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Article Contents

Introduction, 1 smart-home definition, 2 smart-home infrastructures, 3 smart-home energy-management scheme, 4 technical challenges of smart homes, 5 conclusion, conflict of interest.

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Smart homes: potentials and challenges

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Rasha El-Azab, Smart homes: potentials and challenges, Clean Energy , Volume 5, Issue 2, June 2021, Pages 302–315, https://doi.org/10.1093/ce/zkab010

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Decentralized distributed clean-energy sources have become an essential need for smart grids to reduce the harmful effects of conventional power plants. Smart homes with a suitable sizing process and proper energy-management schemes can share in reducing the whole grid demand and even sell clean energy to the utility. Smart homes have been introduced recently as an alternative solution to classical power-system problems, such as the emissions of thermal plants and blackout hazards due to bulk plants/transmission outages. The appliances, sources and energy storage of smart homes should be coordinated with the requirements of homeowners via a suitable energy-management scheme. Energy-management systems are the main key to optimizing both home sources and the operation of loads to maximize home-economic benefits while keeping a comfortable lifestyle. The intermittent uncertain nature of smart homes may badly affect the whole grid performance. The prospective high penetration of smart homes on a smart power grid will introduce new, unusual scenarios in both generation and loading. In this paper, the main features and requirements of smart homes are defined. This review aims also to address recent proposed smart-home energy-management schemes. Moreover, smart-grid challenges with a high penetration of smart-home power are discussed.

Smart homes provide comfortable, fully controlled and secure lifestyles to their occupants. Moreover, smart homes can save energy and money with the possibility of profiting from selling clean renewable energy to the grid. On the other hand, the probable decrease in total domestic-energy loads encourages many governments to support promising smart-home technologies. Some countries have already put out many rules, laws and subsidy programmes to encourage the integration of smart homes, such as encouraging the optimization of the heating system, supporting building energy storage and/or deploying smart meters. For instance, the European Standard EN 15232 [ 1 ] and the Energy Performance of Building Directive 2010/31/EU [ 2 ], which is in line with Directive 2009/72/EC as well as the Energy Road Map 2050 [ 3 ], encourage the integration of smart-home technologies to decrease power demand in residential areas.

To control the environment, a smart home is automated by controlling some appliances, such as those used for lighting and heating, based on different climatic conditions. Now, recent control schemes adapt many functions besides classical switching ones. They can monitor the internal environment and the activities of the home occupants. They also can independently take pre-programmed actions and operate devices in set predefined patterns, independently or according to the user’s requirements. Besides the ease of life, smart homes confirm efficient usage of electricity, lowering peak load, reducing energy bills and minimizing greenhouse-gas emissions [ 4 , 5 ].

Smart homes can be studied from many points of view. The communication systems [ 6 ], social impacts [ 7 ], thermal characteristics [ 8 ], technologies and trends of smart homes [ 9 ] are reviewed individually. Moreover, the monitoring and modelling of smart-home appliances via smart meters are reviewed for accurate load forecasting, as in [ 10 , 11 ]. Recently, power-grid authorities have modified residential electrical tariffs to encourage proper demand-side management by homeowners. Different from previous reviews, this paper introduces smart homes from the electrical/economic point of view. It also discusses smart-home energy-management systems (SHEMS) in two different modes, offline load scheduling and real-time management. The prospective impacts of unusual smart-home power profiles on future smart grids are also summarized.

After this introductory section, Section 1 describes the different definitions of smart homes within the last two decades. Smart-home communication schemes and other infrastructures of smart homes are discussed in Section 2. Section 3 discusses in more detail the existing functions of SHEMS, their pre-proposed optimization techniques and related technical/economical objective functions. The impacts of smart homes on modern grids are also discussed in Section 4. Finally, in Section 5, the main conclusions and contributions of the paper are highlighted.

The term ‘smart home’ has been commonly used for about two decades to describe houses with controlled energy schemes. This automation scheme confirms easier lifestyles for homeowners than normal un-automated homes, especially for elderly or disabled persons. Recently, the concept of ‘smart home’ has a wider description to include many applications of technologies in one place.

Sowah et al. [ 12 ] define smart homes as: ‘Houses that provide their occupants a comfortable, secure, and energy efficient environment with minimum possible costs regardless their occupants.’ The Smart Homes Association defines a smart home as: ‘The integration of technology and services through home networking for a better quality of living’ [ 13 ].

Makhadmeh et al. define them as: ‘Incorporated residential houses with smart technology to improve the comfort level of users (residents) by enhancing safety and healthcare and optimizing power consumption. Users can control and monitor smart-home appliances remotely through the home energy-management system (HEMS), which provides a remote monitoring system that uses telecommunication technology’ [ 14 ].

Smart homes can be defined as: any residential buildings using different communication schemes and optimization algorithms to predict, analyse, optimize and control its energy-consumption patterns according to preset users’ preferences to maximize home-economic benefits while preserving predefined conditions of a comfortable lifestyle.

Distributed clean energy generated by smart homes provides many benefits for prospective smart grids. Consequently, the effects of smart homes on future power grids should be extensively studied. In the near future, smart homes will play a major role as a power supplier in modern grids, not only as a power consumer.

The general infrastructure of smart homes consists of control centres, resources of electricity, smart meters and communication tools, as shown in Fig. 1 . Each component of the smart-home model will be discussed in the following subsections.

Infrastructure of SHEMS source

2.1 The control centre

The control centre provides home users with proper units to monitor and control different home appliances [ 15 ]. All real-time data are collected by SHEMS to optimize the demand/generation coordination and verify the predefined objectives. The main functions of the control centre can be summarized as follows [ 15 ]:

(i) collecting data from different meters, homeowners’ commands and grid utility via a proper communication system;

(ii) providing proper monitoring and analysing of home-energy consumption for homeowners;

(iii) coordinating between different appliances and resources to satisfy the optimal solution for predefined objectives.

2.2 Smart meter

The smart meter receives a demand-response signal from power utilities as an input to the SHEMS system [ 16 , 17 ]. Recently, advanced smart-metering infrastructures can monitor many home features such as electrical consumption, gas, water and heating [ 18 ].

2.3 Appliances

Smart-home loads can be divided according to their operating nature into two categories: schedulable and non-schedulable loads. Non-schedulable loads are operated occasionally according to the homeowner’s desires without any predictable operating patterns, such as printers, televisions and hairdryers, whereas schedulable loads have a predictable operating pattern that can be shifted or controlled via SHEMS, such as washing machines and air conditioners [ 19 ].

According to [ 19 ], controllable devices are also classified into interruptible and non-interruptible load according to the effect of supply interruption on their tasks. Electric vehicles (EVs) can be considered as an exceptional load [ 20 , 21 ]. EVs have two operating modes: charging and discharging. Therefore, EVs are interruptible schedulable loads during the charging mode. Moreover, EV battery energy can also be discharged to supply power to the grid during critical events, which is known as vehicle-to-grid [ 22 ]. By SHEMS, EVs can participate in supplying loads during high-priced power periods. In low-priced power periods, EVs restore their energy from the grid [ 23 , 24 ].

2.4 Resources of electricity

Solar and wind plants are the most mature renewable-energy sources in modern grids. Nowadays, many buildings have installed photovoltaic (PV) modules, thermal solar heaters or micro wind turbines. For smart homes, various functions can be supplied by solar energy besides generating electricity, such as a solar water heater (SWH), solar dryer and solar cooler [ 25 ]. Moreover, PV plants are cheap with low requirements of maintenance [ 26 ], whereas hot water produced by SWHs can be used in many home functions, such as washing and cooking, which increases the home-energy efficiency [ 27 ].

Energy storage may be considered as the cornerstone for any SHEMS. SHEMS are usually installed with energy-storage systems (ESSs) to manage their stored energy according to predefined objectives. Many energy-storage technologies are available in the power markets. Batteries and fuel cells are the most compatible energy-storage types of smart-home applications [ 28 ]. A fuel-cell structure is very similar to a battery. During the charging process, hydrogen fuel cells use electricity to produce hydrogen. Hydrogen feeds the fuel cell to create electricity during the discharging process. Fuel cells have relatively low efficiency compared to batteries. Fuel cells provide extra clean storage environments with the capability of storing extra hydrogen tanks. That perfectly matches isolated homes in remote areas [ 29 ].

Although wind energy is more economical for large-scale plants, it has a very limited market for micro wind turbines in homes. Typically, micro wind turbines require at least a wind speed of 2.7 m/s to generate minimum power, 25 m/s for rated power and 40 m/s for continuous generated power [ 30 ]. A micro wind turbine is relatively expensive, intermittent and needs special maintenance requirements and constraints compared to a solar plant [ 31 ].

Recently, biomass energy has been a promising renewable resource alternative for smart homes. Many pieces of research have recommended biomass energy for different types of buildings [ 32 ]. Heating is the main function of biomass in smart homes, as discussed in [ 33 , 34 ]. In addition, a biomass-fuelled generation system is examined for many buildings [ 35 , 36 ].

2.5 Communication schemes

Recently, communication systems are installed as built-in modules in smart homes. Both home users and grid operators will be able to monitor and control several home appliances in the near future to satisfy the optimum home-energy profile while preserving a comfortable lifestyle. Therefore, both wired and wireless communication schemes are utilized, which is known as a home area network (HAN), to cover remote-control signals as home occupants’ ones. Fig. 1 shows an example of a HAN that consists of Wi-Fi and cloud computing networks for both indoor and outdoor data exchange, respectively [ 37 , 38 ].

Energy-management systems for homes require three main components: the computational embedded controllers, the local-area network communication middleware and the transmission control protocol/internet protocol (TCP/IP) communication for wide-area integration with the utility company using wide-area network communication [ 37 ].

According to home characteristics, many wired communication schemes can be selected, such as power-line communication (PLC), inter-integrated circuit (I2C) and serial peripheral interface or wireless technologies such as Zigbee, Wi-Fi, radio-frequency identification (RFID) and the Internet of Things (IoT) to develop HANs. A few of the most common techniques will be discussed briefly in the following subsections [ 38 ].

PLC is a technique that uses power lines to transmit both power and data via the same cable to customers simultaneously. Such wired schemes provide fast communication with low interference of data. Moreover, PLC provides many communication terminals, as all power plugs can be used for data transferring. As all electrical home devices are connected by power cables, PLC can communicate with all these devices via the same cable.

PLC set-up has a low cost, as it uses pre-installed power cables with minimum hardware requirements. With a PLC communication scheme, home controllers can also be integrated easily with a high speed of data transfer. On the other hand, PLC has a high probability of data-signal attenuation. Furthermore, data signals suffer from electromagnetic interference of transmitted power signals.

2.5.2 Zigbee

Zigbee is a wireless communication technique [ 37–46 ]. Zigbee follows the IEEE 802.15.4 standard as a radio-frequency wireless communication scheme. It does not require any licenses for limited zones such as homes [ 37 ]. Also, Zigbee is a low-power-consuming technique. Therefore, it is suitable for basic home appliances, such as lighting, alarm systems and air conditioners [ 39 , 40 ]. Zigbee usually considers all home devices as slaves with a master coordinator/controller, which is known as a master–slave architecture.

Zigbee provides highly secured transferred data [ 38 , 41 ] with high reliability and capacity [ 42 ]. It also has self-organizing capabilities [ 42 ]. Conversely, Zigbee is relatively expensive due to special hardware requirements with low data-transfer rates. Moreover, Zigbee is not compatible with many other protocols, such as internet-supported protocols and Wi-Fi.

2.5.3 Wi-Fi technology

Wi-Fi is a wireless communication technique that follows the IEEE 802.11 standard. Wi-Fi provides high-rate data transfer that is compatible with many information-based devices such as computers, laptops, etc. [ 43 , 44 ].

Wi-Fi is a highly secured scheme with many of the familiar internet capabilities and low data-transfer delays (<3 ms) [ 45 ]. On the contrary, it is a relatively high-power-consuming scheme compared to Zigbee schemes [ 45 ]. Also, home devices can affect transmitted data signals by their emitted electromagnetic fields [ 46 ]. Wi-Fi can also suffer from interference from other communication protocols such as Zigbee and Bluetooth [ 43 ].

RFID is a wireless communication technique that conforms to the electronic product code protocol [ 47–52 ]. It can coincide with other communication schemes such as Wi-Fi and Zigbee. It can be utilized for a relatively widespread range of frequencies, from 120 kHz to 10 GHz. It also covers a wide range of distances, from 10 cm to 200 m [ 48 ]. Many researchers are investigating RFID home applications, such as energy-management systems [ 49 ], door locks [ 50 ] and lighting controls [ 51 ].

RFID operates on tags and reader-identification systems with a high data-transfer rate. Nevertheless, RFID has expensive chips with low bandwidth. The possibility of tag collision within the same zone decreases the accuracy of the RFID scheme.

This scheme connects home devices, users and grid operators via the internet to monitor and manage smart homes [ 6 , 38 , 53–65 ]. Consequently, the IoT and cloud computing have proven to be cheap, popular and easy services for smart homes. Moreover, IoT schemes are compatible with many other communication protocols, such as Zigbee, Bluetooth, etc., as listed in Table 1 . Internet hacking is the main problem with IoT schemes. System security and privacy are critical challenges for such internet-based schemes.

IoT protocols features

Today, building energy-management systems (BEMS) are utilized within residential, commercial, administration and industrial buildings. Moreover, the integration of variable renewable-energy sources with proper ESSs deployed in buildings represents an essential need for reliable, efficient BEMS.

For small-scale residential buildings or ‘homes’, BEMS should deal with variable uncertain load behaviours according to the home occupants’ desires and requirements, which is known as SHEMS. Throughout recent decades, many SHEMS have been presented and defined in many research studies.

In [ 66 ], SHEMS are defined as services that efficiently monitor and manage electricity generation, storage and consumption in smart houses. Nazabal et al. [ 67 ] include a collaborative exchange between smart homes and the utility as a main function of SHEMS. In [ 68 ], SHEMS are defined from the electrical-grid point of view as important tools that provide several benefits such as flattening the load curve, a reduction in peak demand and meeting the demand-side requirements.

3.1 Functions of SHEMS

Adaptive SHEMS are required to conserve power, especially with the increasing evolution in home loads. SHEMS should control both home appliances and available energy resources according to the real-time tariff and home user’s requirements [ 4 ]. Home-management schemes should provide an interface platform between home occupants and the home controller to readjust occasionally the load priority [ 5 ].

As shown in Fig. 2 , the majority of smart-home centres can be summarized as having five main functions [ 5 ], as follows:

Functions of SHEMS

(i) Monitoring: provides home residents with visual instantaneous information about the consumed power of different appliances and the status of several home parameters such as temperature, lights, etc. Furthermore, it can guide users to available alternatives for saving energy according to the existing operating modes of different home appliances.

(ii) Logging: collects and saves data pertaining to the amount of electricity consumed by each appliance, generated out of energy-conservation states. This functionality includes analysing the demand response for real-time prices.

(iii) Control: both direct and remote-control schemes can be implemented in smart homes. Different home appliances are controlled directly by SHEMS to match the home users’ desires, whereas other management functions are controlled remotely via cell phones or laptops, such as logging and controlling the power consumption of interruptible devices.

(iv) Management: the main function of SHEMS. It concerns the coordination between installed energy sources such as PV modules, micro wind turbines, energy storage and home appliances to optimize the total system efficiency and/or increase economic benefits.

(v) Alarms: SHEMS should respond to specific threats or faults by generating proper alarms according to fault locations, types, etc.

3.2 Economic analysis

Economic factors affecting home-management systems are classified into two classes. First, sizing costs include expanses of smart-home planning. Second, operating costs consist of bills of consumed energy. These costs depend mainly on the electrical tariff.

3.2.1 Sizing costs

These include capital, maintenance and replacement costs of smart-home infrastructures, such as PV systems, wind turbines, batteries/fuel cells and communication systems. In most previous SHEMS, such planning costs usually are not taken into consideration, as management schemes usually concern the daily operating costs only [ 69 ].

3.2.2 Operating costs

The electricity tariff is the main factor that gives an indication of the value of saving energy, according to the governmental authority; there are many types of tariffs, as follows [ 70–74 ]:

(i) Flat tariffs: the cost of consumed energy is constant regardless of the continuous change in the load. Load-rescheduling schemes do not affect the electricity bills in this scheme. Therefore, homeowners are not encouraged to rearrange their consumed energy, as they have no any economic benefits from managing the consumption of their appliances.

(ii) Block-rate tariffs: in this scheme, the monthly consumed energy price is classified into different categories. Each category has its own flat-rate price. Therefore, the main target of SHEMS is minimizing the total monthly consumed energy to avoid the risk of high-priced categories.

(iii) Seasonal tariffs: in this scheme, the total grid-demand load is changed significantly from one season to another. Therefore, the utility grid applies a high flat-rate tariff in high-demand seasons and vice versa. SHEMS should minimize the total consumption in such high-priced seasons and get the benefit of consumption in low-priced seasons.

(iv) Time-of-use (TOU) tariff: there are two or three predefined categories of tariffs daily in this scheme. First, a high-priced-hours tariff is applied during high-demand hours, which is known as a peak-hours tariff. Second, an off-peak-hours tariff is applied during low-demand hours with low prices for energy consumption. Sometimes, three levels of pricing are defined by the utility grid during the day, i.e. off-, middle- and high-peak costs, as discussed in [ 75 ]. SHEMS shift interruptible loads with low priority to off-peak hours to minimize the bill.

(v) Super peak TOU: this can be considered as a special case of the previously described TOU tariff but with a short peak-hours period of ~4 hours daily.

(vi) Critical peak pricing (CPP): the utility grid uses this tariff scheme during expected critical events of increasing the gap between generation and power demand. The price is increased exceptionally during these critical events by a constant predefined rate.

(vii) Variable peak pricing: this is a subcategory of the CPP tariff in which the exceptional increase in the tariff is variable. The utility grid informs consumers of the exceptional dynamic price increase according to its initial expectations.

(viii) Real-time pricing (RTP): the price is changing continuously during pre-identified intervals that range from several minutes to an hour. This tariff is the riskiest pricing scheme for homeowners. The electricity bill can increase significantly without a proper management system. SHEMS should communicate with grid utility and reschedule both home appliances, sources and energy storage continuously to minimize the total bill.

(viii) Peak-time rebates (PTRs): a proper price discount is considered for low-consumption loads during peak hours, which can be refunded later by the grid.

Depending on the electricity tariff, SHEMS complexity varies dramatically. In the case of using a flat-rate tariff, the algorithm becomes simpler, as one value is recorded for selling or buying the electricity. Tariffs may be published from the proper authority or predicted according to historical data. Prediction of the dynamic tariff is a main step in any SHEMS. Many time frames of tariff prediction are proposed that vary from hourly, daily or even a yearly prediction. Many optimization techniques with various objective functions are proposed to handle different features of both smart-home infrastructures and electricity tariffs, as will be discussed in the following section.

3.3 Pre-proposed SHEMS

Different SHEMS may be classified according to four features: operational planning of load-scheduling techniques, system objective functions, optimization techniques and smart-home model characteristics, as will be discussed in the following subsections.

3.3.1 Load-scheduling techniques

SHEMS concern the generation/load power balance to provide a comfortable lifestyle with the minimum possible costs. Scheduling loads according to their priority and the periods of renewable energy (solar, wind and EV state) can help in reducing the overall energy consumption daily. According to data collected by the management system, an initial load schedule is suggested daily to minimize the daily cost of consumed energy [ 76 ].

By using a proper optimal scheduling algorithm, electricity bills can be reduced by shifting loads from high-priced to low-priced intervals [ 77 , 78 ]. Many techniques have been proposed for home load scheduling, as will be discussed in the following subsections:

(i) Rule-based scheduling: in this algorithm, all home appliances and resources are connected to smart data-collector taps. By processing the collected data, different appliances are scheduled according to their priorities and based on the if/then rule. Also, some high-priority loads are supplied by home renewable sources/storage to maintain their function during predicted peak hours [ 79 , 80 ].

(ii) Artificial intelligence (AI): many AI controllers have been proposed for home load scheduling, such as artificial neural networks (ANNs), fuzzy logic (FL) and adaptive neural fuzzy inference systems (ANFISs). Table 2 compares between the three types of scheduling scheme based on AI.

Optimization techniques for load scheduling

3.3.2 Objective functions

(i) Single-objective techniques: in these schemes, only one criterion is minimized or maximized according to the home-user requirements. Several minimization objective functions were proposed, as follows:

lifetime degradation [ 47–49 ];

life-cycle costs [ 93 ];

gas emissions [ 94–96 ];

both active and reactive losses [ 97 , 98 ].

On the other hand, some research defined other single maximizing objective functions, such as:

net present value [ 96 ].

economic profits [ 97 , 98 ].

increased system reliability: according to many well-known reliability indices, such as loss of power supply probability, loss of load probability and others [ 99 , 100 ].

generated power [ 101 , 102 ].

loadability [ 103 ];

Multi-objective techniques: homeowners may have several criteria to be optimized together. Multi-objective optimization (MOO) problems consider many functions simultaneously. MOO finds a proper coordination that moderately satisfies the considered objectives. In [ 102 ], SHEMS with MOO techniques are summarized. Table 3 lists some examples of such multi-objective functions.

Multi-objective functions of SHEMS

3.3.3 Optimization techniques

Optimization techniques aim usually to identify the best coordination taking into consideration predefined constraints. Many approaches are available for addressing optimization problems. These approaches can be classified into two categories: classical and AI-based techniques. Table 4 lists various SHEMS optimization techniques and their main features.

Optimization techniques in SHEMS

Classical methods, especially linear programming types, have been usually applied in the last decade for smart homes with limited objective functions and simple model characteristics of tariff and home appliances. Recently, AI-based techniques have been proposed to cover more complicated models of smart homes with multi-objective functions with high levels of comfortable lifestyles.

3.3.4 Home-model characteristics

The smart-home model differs significantly according to three factors: installed variable energy sources, applied tariff and EV deployment. PV systems have been applied for nearly all studied smart homes due to their low price, simplicity of installation, low maintenance requirements and easily predicted daily power profile. On the other hand, a few pieces of research have considered micro wind turbines in their home models, such as [ 120 ]. Wind turbines are limited by high-wind-speed zones that are usually located in rural areas. In addition, homeowners usually do not prefer wind turbines due to their high prices, mechanical maintenance requirements and the unpredictable variation in wind power.

Dynamic tariffs are applied in most smart-home research. Specifically, the TOU tariff is analysed in a lot of studies, such as [ 121 , 122 ], whereas little research uses RTP, such as [ 123 , 124 ]. EV is studied as an energy source in the parking period or vehicle-to-grid (V2G) mode. In [ 75 , 125 ], EV in V2G mode reduces the electricity bill in peak hours, whereas, in [ 126–130 ], ESSs are managed only to reduce the electricity usage from the grid.

Many technical challenges arise for modern grids due to the increasing mutual exchange between smart homes and utility grids, especially power-quality control. Electric-power-quality studies usually confirm the acceptable behaviour of electrical sources such as voltage limits and harmonics analysis. Recently, smart power grids have diverse generation sources from different technologies that depend mainly on power electronics devices that increase the difficulty in power-quality control. Power-quality constraints should be taken into consideration for any energy-management systems to provide harmony between modern sources and loads.

On the other hand, power-quality issues should not form an additional obstacle against the integration of new technologies in modern grids. Therefore, both advanced communication schemes and AI-based techniques make modern grids ‘smart’ enough to cope with selective power-quality management. Smart homes exchange power with utility grids. With the prospective increase in such smart homes, the effect of their behaviour should be studied and controlled. Smart homes affect the grid-power quality in three different areas, as will be discussed in the following paragraphs [ 154–156 ].

4.1 Generating equipment

Integrated micro generation schemes in smart homes are mainly single-phase sources based on inverters with high switching frequencies that reach to many kHz. Low-order harmonics of such a generation type can usually be disregarded. However, with the expected continuous increase in such micro generators, the harmonics of low-voltage networks may shift into a range of higher frequencies, perhaps from 2 to 9 kHz [ 157 ]. Therefore, more research is needed to re-evaluate the appropriate limits for generation equipment in smart homes. Moreover, single-phase generation increases the risk of an unbalanced voltage in low-voltage grids. Therefore, negative-sequence voltage limits should be re-evaluated particularly for weak distribution networks. Also, a need for zero-sequence voltage limits may arise [ 154 ].

4.2 Home appliances

Modern home appliances depend mainly on electronic devices, such as newer LED lighting systems, EV battery chargers, etc., with relatively low fundamental current and high harmonic contents compared to traditional ones. According to many power-system analysers, many harmonics will increase significantly to risky levels, particularly fifth-harmonic voltage, with increase in such new electronic appliances [ 155 ].

4.3 Distribution network

In future grids, significant unusual operating scenarios may be possible with high penetration of domestic generation, especially with the possibility of an islanded (self-balanced) operation of smart homes. Short-circuit power will differ significantly during different operating conditions compared to classical grids. Moreover, low-voltage networks may suffer from damping-stability problems due to the continuous decrease in resistive loads, in conjunction with the increase in capacitive loads of electronic equipment. In addition, resonance problems may occur with low frequencies according to the continuous change in the nature of the load [ 156 ].

Although smart homes have bad impacts on utility grids, there are no charges applied from the grid authority to homeowners based on their buildings’ effects on grid-power quality. Therefore, home planners and SHEMS designers are usually concerned only with the economic benefits of their proposed schemes.

Smart homes, using new revolutions in communication systems and AI, provide residential houses with electrical power of a dual nature, i.e. as producer and consumer or ‘prosumer’. The energy-management system includes many components that mainly depend on a suitable communication scheme to coordinate between available sources, loads and users’ desire. Among many proposed communication systems, the IoT has many advantages and was chosen in many studies. Besides the popularity of the IoT, it does not need any special equipment installation and is compatible with many other communications protocols.

Many functions are applied by management systems such as monitoring and logging to facilitate a proper interaction between home occupants and the management scheme. Home security also should be confirmed via the management scheme by using different alarms corresponding to preset threats. Home users control different home appliances according their desires by SHEMS and via cell phones or manually.

The electricity tariff plays an important role in defining management-system characteristics. Tariffs vary from simple fixed flat rates to complicated variable dynamic ones according to the electrical-grid authority’s rules for residential loads. According to the tariff and selected objective functions, pre-proposed optimization techniques vary significantly from simple classical linear programming to sophisticated AI ones.

Modern electronic-based home appliances increase power-grid-quality problems, such as high harmonic contents, unbalanced loading and unpredictable short-circuit currents. On the other hand, power-grid authorities do not charge homeowners according to their buildings’ effects on the power quality. Therefore, all proposed energy-management systems are concerned mainly with the economic profits from reducing electricity consumption or even selling electrical power to the utility grids. In the future, price-based power-quality constraints should be defined by the grid authorities to confirm proper power exchange between both smart homes and grids. A possible future direction is behaviour modelling of aggregated smart homes/smart cities in different operating scenarios to conclude probable power-grid scenarios for stability and quality.

This work was supported by the project entitled ‘Smart Homes Energy Management Strategies’, Project ID: 4915, JESOR-2015-Cycle 4, which is sponsored by the Egyptian Academy of Scientific Research and Technology (ASRT), Cairo, Egypt.

None declared.

Comité Européen de Normalisation . Energy Performance of Buildings—Impact of Building Automation, Control, and Building Management; European Technical Standard EN 15232 ; CEN: Brussels, Belgium . 2012 . http://www.cres.gr/greenbuilding/PDF/prend/set4/WI_22_TC-approval_version_prEN_15232_Integrated_Building_Automation_Systems.pdf ( 20 December 2020 , date last accessed).

European Parliament . Directive 2010/31/EU of the European Parliament and of the Council of 19 May 2010 on the Energy Performance of Buildings; Directive 2010/31/EU ; The European Parliament and the Council of the European Union: Brussels, Belgium . 2010 . https://eurlex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:153:0013:0035:en:PDF ( 20 December 2020 , date last accessed).

European Climate Foundation . Roadmap 2050 Project .   http://www.roadmap2050.eu/ ( 20 December 2020 , date last accessed).

Al-Ali   AR , El-Hag   A , Bahadiri   M , et al.    Smart home renewable energy management system . Energy Procedia , 2011 , 12 : 120 – 126 .

Google Scholar

van Dam   S , Bakker   CA , Buiter   J . Do home energy management systems make sense? Assessing their overall lifecycle impact . Energy Policy,   2013 , 63 : 398 – 407 .

Kuzlu   M , Pipattanasomporn   M , Rahman   S . Review of communication technologies for smart homes/building applications. In: 2015 IEEE Innovative Smart Grid Technologies—Asia (ISGT ASIA) , Bangkok, Thailand , 3–6 November 2015 , 1 – 6 .

Wilson   C , Hargreaves   T , Hauxwell-Baldwin   R . Smart homes and their users: a systematic analysis and key challenges . Personal and Ubiquitous Computing , 2015 , 19 : 463 – 476 .

Schieweck   A , Uhde   E , Salthammer   T , et al. .   Smart homes and the control of indoor air quality . Renewable and Sustainable Energy Reviews,   2018 , 94 : 705 – 718 .

Nacer   A , Marhic   B , Delahoche   L . Smart home, smart HEMS, smart heating: an overview of the latest products and trends. In: 2017 6th International Conference on Systems and Control (ICSC) , Batna, Algeria , 7–9 May 2017 , 90 – 95 .

Yuan   X , Han   P , Duan   Y , et al. .   Residential electrical load monitoring and modeling—state of the art and future trends for smart homes and grids . Electric Power Components and Systems , 2020 , 48 : 1125 – 1143 .

Wang   Y , Chen   Q , Hong   H , et al. .   Review of smart meter data analytics: applications, methodologies, and challenges . IEEE Transactions on Smart Grid , 2019 , 10 : 3125 – 3148 .

Sowah   RA , Ofoli   AR , Tetteh   MK , et al. .   Demand side management of smart homes using OpenHAB framework for interoperability of devices. In: 2018 IEEE 7th International Conference on Adaptive Science & Technology (ICAST) , Accra, Ghana , 22–24 August 2018 , 1 – 8 .

Robles   RJ , Kim   T . Applications, systems and methods in smart home technology: a review . Int. J. Adv. Sci. Technol. , 2010 , 15 : 37 – 48 .

Makhadmeh   SN , Khader   AT , Al-Betar   MA , et al. .   Optimization methods for power scheduling problems in smart home: survey . Renewable and Sustainable Energy Reviews , 2019 , 115 : 109362 .

Zhao   Z , Lee   WC , Shin   Y , et al. .   An optimal power scheduling method for demand response in home energy management system . IEEE Transactions on Smart Grid , 2013 , 4 : 1391 – 1400 .

Benzi   F , Anglani   N , Bassi   E , et al. .   Electricity smart meters interfacing the households . IEEE Transactions on Industrial Electronics , 2011 , 58 : 4487 – 4494 .

Depuru   SR , Wang   L , Devabhaktuni   V , et al. .   Smart meters for power grid — challenges, issues, advantages and status. In: 2011 IEEE/PES Power Systems Conference and Exposition , Phoenix, AZ (USA) , 20–23 March 2011 , 1 – 7 .

Zheng   J , Gao   W , Lin   L . Smart meters in smart grid: an overview. In: IEEE Green Technologies Conference , Denver, Colorado, USA , 4–5 April 2013 , 57 – 64 .

Chavali   P , Yang   P , Nehorai   A . A distributed algorithm of appliance scheduling for home energy management system . IEEE Transactions on Smart Grid , 2014 , 5 : 282 – 290 .

Ma   Y , Houghton   T , Cruden   A , et al. .   Modeling the benefits of vehicle-to-grid technology to a power system . IEEE Transactions on power systems , 2012 , 27 : 1012 – 1020 .

Yiyun   T , Can   L , Lin   C , et al. .   Research on vehicle-to-grid technology. In: International Conference on Computer Distributed Control and Intelligent Environmental Monitoring , Changsha, Hunan, China , 19–20 February 2011 , 1013 – 1016 .

Kempton   W , Tomić   J . Vehicle-to-grid power fundamentals: calculating capacity and net revenue . Journal of Power Sources , 2005 , 144 : 268 – 279 .

Makhadmeh   SN , Khader   AT , Al-Betar   MA , et al. .   A novel hybrid grey wolf optimizer with min-conflict algorithm for power scheduling problem in a smart home . Swarm and Evolutionary Computation , 2021 , 60 : 100793 .

Makhadmeh   SN , Khader   AT , Al-Betar   MA , et al. .   Multi-objective power scheduling problem in smart homes using grey wolf optimizer . Journal of Ambient Intelligence and Humanized Computing , 2019 , 10 : 3643 – 3667 .

Parida   B , Iniyan   S , Goic   R . A review of solar photovoltaic technologies . Renewable and Sustainable Energy Reviews , 2011 , 15 : 1625 – 1636 .

Schwerin   A . Analysis of the potential solar energy market in the Caribbean . REPOSITORIO NACIONAL CONACYT . 2010 . https://www.solarthermalworld.org/sites/default/files/story/2015-04-06/solar_market_analysis_caribbean.pdf ( 20 December 2020 , date last accessed).

Brown   CE.   World Energy Resources . Berlin : Springer Verlag , 2002 .

Google Preview

Wan   C , Zhao   J , Song   Y , et al. .   Photovoltaic and solar power forecasting for smart grid energy management . CSEE Journal of Power and Energy Systems , 2015 , 1 : 38 – 46 .

Ewais   AM , El-Azab   R , Adma   MAA . Stand-alone microgrid energy storage schemes: comparative study. In: 2018 Twentieth International Middle East Power Systems Conference (MEPCON) , Cairo, Egypt , 18–20 December 2018 , 564 – 569 .

Fthenakis   V , Kim   HC . Land use and electricity generation: a life-cycle analysis . Renewable and Sustainable Energy Reviews , 2009 , 13 : 1465 – 1474 .

Lei   M , Shiyan   L , Chuanwen   J , et al. .   A review on the forecasting of wind speed and generated power . Renewable and Sustainable Energy Reviews , 2009 , 13 : 915 – 920 .

Mazen   R , Radwan   M , Abdel-Samiea   M . Utilization of biomass energy in high-rise buildings. In: 2013 4th International Youth Conference on Energy (IYCE) , Siófok, Hungary , 6–8 June 2013 , 1 – 3 .

Carpio   M , Zamorano   M , Costa   M . Impact of using biomass boilers on the energy rating and CO 2 emissions of Iberian Peninsula residential buildings . Energy and Buildings , 2013 , 66 : 732 – 744 .

Berković-Šubić   M , Rauch   M , Dović   D , et al. .   Primary energy consumption of the dwelling with solar hot water system and biomass boiler . Energy Conversion and Management , 2014 , 87 : 1151 – 1161 .

Huang   Y , Wang   Y , Rezvani   S , et al. .   Biomass fuelled trigeneration system in selected buildings . Energy Conversion and Management , 2011 , 52 : 2448 – 2454 .

Wu   G , Yu   X . Remote control system for energy efficient home. In: 2013 IEEE Energytech , Cleveland, OH, USA , 21–23 May 2013 , 1 – 5 .

Safaric   S , Malaric   K . ZigBee wireless standard. In: Proceedings ELMAR 2006 , Zadar, Croatia , 7–10 June 2006 , 259 – 262 .

Huq   MZ , Islam   S . Home Area Network technology assessment for demand response in smart grid environment. In: 2010 20th Australasian Universities Power Engineering Conference , Christchurch, New Zealand , 5–8 December 2010 , 1 – 6 .

Dou   N , Mei   Y , Yanjuan   Z , Yan   Z . The networking technology within smart home system—ZigBee technology. In: 2009 International Forum on Computer Science-Technology and Applications , Chongqing, China , 25–27 December 2009 , 29 – 33 .

Ajgaonkar   P , Wang   L , Alam   M . Simulation studies on ZigBee communications for home automation and networking. In: 2010 IEEE AUTOTESTCON , Orlando, FL, USA , 13–16 September 2010 , 1 – 6 .

Li   Y , Zhang   K , Zhang   X . Research on application of ZigBee technology in flammable and explosive environment . In: 2009 First International Conference on Information Science and Engineering , Nanjing, China , 26–28 December 2009 , 4074 – 4078 .

Khan   SA , Khan   FA , Shahid   A , et al. .   Zigbee based reconfigurable clustered home area network. In: 2009 Third International Conference on Sensor Technologies and Applications , Athens, Greece , 18–23 June 2009 , 32 – 37 .

Han   T , Han   B , Zhang   L , et al. .   Coexistence study for WiFi and ZigBee under smart home scenarios. In: 2012 3rd IEEE International Conference on Network Infrastructure and Digital Content , Beijing, China , 21–23 September 2012 , 669 – 674 .

Sarijari   MA , Lo   A , Abdullah   MS , et al. .   Coexistence of heterogeneous and homogeneous wireless technologies in smart grid-home area network. In: 2013 International Conference on Parallel and Distributed Systems , Seoul, South Korea , 15–18 December 2013 , 576 – 581 .

Kounev   V , Tipper   D . Advanced metering and demand response communication performance in Zigbee based HANs. In: 2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) , Turin, Italy , 14–19 April 2013 , 31 – 36 .

Batista   NC , Melício   R , Matias   JCO , Catalão   JPS . ZigBee wireless area network for home automation and energy management: field trials and installation approaches. In: 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe) , Berlin, Germany , 14–17 October 2012 , 1 – 5 .

Salazar   J.   Wireless Networks . 1st edn. Prague : Czech Technical University of Prague Faculty of electrical engineering , 2017 .

Phillips   T , Karygiannis   T , Kuhn   R . Security standards for the RFID market . IEEE Security & Privacy , 2005 , 3 : 85 – 89 .

Li   Y . Design of a key establishment protocol for smart home energy management system. In: 2013 Fifth International Conference on Computational Intelligence, Communication Systems and Networks , Madrid, Spain , 5–7 June 2013 , 88 – 93 .

Park   YT , Sthapit   P , Pyun   J . Smart digital door lock for the home automation. In: TENCON 2009—2009 IEEE Region 10 Conference , Singapore , 23–26 November 2009 , 1 – 6 .

Hussain   S , Schaffner   S , Moseychuck   D . Applications of wireless sensor networks and RFID in a smart home environment. In: 2009 Seventh Annual Communication Networks and Services Research Conference , Moncton, NB, Canada , 11–13 May 2009 , 153 – 157 .

Yao   W , Chu   C , Li   Z . The use of RFID in healthcare: benefits and barriers. In: 2010 IEEE International Conference on RFID-Technology and Applications , Guangzhou, China , 17–19 June 2010 , 128 – 134 .

Wang   C , Li   X , Liu   Y , Wang   H . The research on development direction and points in IoT in China power grid. In: 2014 International Conference on Information Science, Electronics and Electrical Engineering , Sapporo, Japan , 2–4 July 2014 , 245 – 248 .

Chettri   L , Bera   R . A comprehensive survey on Internet of Things (IoT) toward 5G wireless systems . IEEE Internet of Things Journal , 2020 , 7 : 16 – 32 .

Samuel   SSI . A review of connectivity challenges in IoT-smart home. In: 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC) , Muscat, Oman , 15–16 March 2016 , 1 – 4 .

Withanage   C , Ashok   R , Yuen   C , Otto   K . A comparison of the popular home automation technologies. In: 2014 IEEE Innovative Smart Grid Technologies—Asia (ISGT ASIA) , Kuala Lumpur, Malaysia , 20–23 May 2014 , 600 – 605 .

Zhu   YH , Qiu   S , Chi   K , Fang   Y . Latency aware IPv6 packet delivery scheme over IEEE 802.15.4 based battery-free wireless sensor networks . IEEE Transactions on Mobile Computing , 2017 , 16 : 1691 – 1704 .

Yi   P , Iwayemi   A , Zhou   C . Developing Zigbee deployment guideline under Wi-Fi interference for smart grid applications . IEEE Transactions on Smart Grid , 2011 , 2 : 110 – 120 .

Mincov   N , Zanatta   L , Lopes   JA , Lôbo   M . Communication technologies for differentiated smart grid environments. In: 2013 IEEE PES Conference on Innovative Smart Grid Technologies (ISGT Latin America) , Sao Paulo, Brazil , 24–27 February 2013 , 1 – 4 .

Chhaya   L , Sharma   P , Bhagwatikar   G , Kumar   A . Wireless sensor network based smart grid communications: cyber attacks, intrusion detection system and topology control . Electronics , 2017 , 6 : 5 .

Gungor   VC , Hancke   GP . Industrial wireless sensor networks: challenges, design principles, and technical approaches . IEEE Transactions on Industrial Electronics , 2009 , 56 : 4258 – 4265 .

Liu   Y . Wireless sensor network applications in smart grid: recent trends and challenges . International Journal of Distributed Sensor Networks , 2012 , 8 : 492819 .

Al-Sarawi   S , Anbar   M , Alieyan   K , Alzubaidi   M . Internet of Things (IoT) communication protocols: review. In: 2017 8th International Conference on Information Technology (ICIT) , Amman, Jordan , 17–18 May 2017 , 685 – 690 .

Li   Y , Cheng   X , Cao   Y , et al.    Smart choice for the smart grid: narrowband Internet of Things (NB-IoT) . IEEE Internet of Things Journal , 2018 , 5 : 1505 – 1515 .

Ratasuk   RR , Vejlgaard   B , Mangalvedhe   N , Ghosh   A . NB-IoT system for M2M communication. In: 2016 IEEE Wireless Communications and Networking Conference Workshops (WCNCW) , Doha, Qatar , 3–6 April 2016 , 428 – 432 .

Son   Y , Moon   K . Home energy management system based on power line communication. In: 2010 Digest of Technical Papers International Conference on Consumer Electronics (ICCE) , Las Vegas, NV, USA , 9–13 January 2010 , 115 – 116 .

Nazabal   JA , Falcone   FJ , Fernandez-Valdivielso   C , et al.    Energy Management System proposal for efficient smart homes. In: 2013 International Conference on New Concepts in Smart Cities: Fostering Public and Private Alliances (SmartMILE) , Gijon, Spain , 11–13 December 2013 , 1 – 5 .

Boynuegri   AR , Yagcitekin   B , Baysal   M , et al.    Energy management algorithm for smart home with renewable energy sources. In: 4th International Conference on Power Engineering, Energy and Electrical Drives , Istanbul, Turkey , 13–17 May 2013 , 17531758 .

Torriti   J . Price-based demand side management: assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy . Energy , 2012 , 44 : 576 – 583 .

Asadinejad   A , Tomsovic   K . Optimal use of incentive and price based demand response to reduce costs and price volatility . Electric Power Systems Research , 2017 , 144 : 215 – 223 .

Hart   DG . Using AMI to realize the Smart Grid. In: 2008 IEEE Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century , Pittsburgh, PA, USA , 20–24 July 2008 , 1 – 2 .

Aigner   DJ , Leamer   EE . Estimation of time-of-use pricing response in the absence of experimental data: an application of the methodology of data transferability . Journal of Econometrics , 1984 , 26 : 205 – 222 .

de Sá Ferreira   R , Barroso   LA , Lino   PR , et al.    Time-of-use tariff design under uncertainty in price-elasticities of electricity demand: a stochastic optimization approach . IEEE Transactions on Smart Grid , 2013 , 4 : 2285 – 2295 .

Dutta   G , Mitra   K . A literature review on dynamic pricing of electricity . J Oper Res Soc , 2017 , 68 : 1131 – 1145 .

Erdinc   O , Paterakis   NG , Mendes   TDP , et al.    Smart household operation considering Bi-directional EV and ESS utilization by real-time pricing-based DR . IEEE Transactions on Smart Grid , 2015 , 6 : 1281 – 1291 .

Marzband   M , Alavi   H , Ghazimirsaeid   S , et al.    Optimal energy management system based on stochastic approach for a home microgrid with integrated responsive load demand and energy storage . Sustainable Cities and Society , 2017 , 28 : 256 – 264 .

Patel   K , Khosla   A . Home energy management systems in future smart grid networks: a systematic review. In: 2015 1st International Conference on Next Generation Computing Technologies (NGCT) , Dehradun, India , 4–5 September 2015 , 479 – 483 .

Zhou   B , Li   W , Chan   KW , et al.    Smart home energy management systems: concept, configurations, and scheduling strategies . Renewable and Sustainable Energy Reviews , 2016 , 61 : 30 – 40 .

Kawakami   T , Yoshihisa   T , Fujita   N , Tsukamoto   M . A rule-based home energy management system using the Rete algorithm. In: 2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE) , Tokyo, Japan , 1–4 October 2013 , 162 – 163 .

Yoshihisa   T , Fujita   N , Tsukamoto   M . A rule generation method for electrical appliances management systems with home EoD. In: The 1st IEEE Global Conference on Consumer Electronics , Tokyo, Japan , 2–5 October 2012 , 248 – 250 .

Yuce   B , Rezgui   Y , Mourshed   M . ANN–GA smart appliance scheduling for optimised energy management in the domestic sector . Energy and Buildings , 2016 , 111 : 311 – 325 .

Gharghan   SK , Nordin   R , Ismail   M , Abd Ali   J . Accurate wireless sensor localization technique based on hybrid PSO-ANN algorithm for indoor and outdoor track cycling . IEEE Sensors Journal , 2015 , 16 : 529 – 541 .

Ahmed   MS , Mohamed   A , Homod   RZ , Shareef   H . Hybrid LSA-ANN based home energy management scheduling controller for residential demand response strategy . Energies , 2016 , 9 : 716 .

Onder   Z , Sezer   S , Çanak   I . A Tauberian theorem for the weighted mean method of summability of sequences of fuzzy numbers . Journal of Intelligent and Fuzzy Systems , 2015 , 28 : 1403 – 1409 .

Wu   Y , Zhang   B , Lu   J , et al.    Fuzzy logic and neuro-fuzzy systems: a systematic introduction . International Journal of Artificial Intelligence and Expert Systems , 2011 , 2 : 2011 – 2047 .

Hong   YY , Lin   JK , Wu   CP , Chuang   CC . Multi-objective air-conditioning control considering fuzzy parameters using immune clonal selection programming . IEEE Transactions on Smart Grid , 2012 , 3 : 1603 – 1610 .

Mohsenzadeh   A , Shariatkhah   M , Haghifam   MR . Applying fuzzy techniques to model customer comfort in a smart home control system. In: 22nd International Conference and Exhibition on Electricity Distribution (CIRED 2013) , Stockholm, Sweden , 10–13 June 2013 , 1 – 4 .

Ciabattoni   L , Grisostomi   M , Ippoliti   G , et al.    Home energy management benefits evaluation through fuzzy logic consumptions simulator. In: Proceedings of the International Joint Conference on Neural Networks . Beijing, China , 6–11 July 2014 .

Wu   Z , Zhou   S , Li   J , et al.    Real-time scheduling of residential appliances via conditional risk-at-value . IEEE Transactions on Smart Grid , 2014 , 5 : 1282 – 1291 .

Ainsworth   N , Johnson   B , Lundstrom   B . A fuzzy-logic subsumption controller for Home Energy Management Systems. In: 2015 North American Power Symposium (NAPS) , Charlotte, NC, USA , 4–6 October 2015 , 1 – 7 .

Wu   Z , Zhang   XP , Brandt   J ,   et al . Three control approaches for optimized energy flow with home energy management system . IEEE Power and Energy Technology Systems Journal , 2015 , 2 : 21 – 31 .

Choi   IH , Yoo   SH , Jung   JH , et al.    Design of Neuro-Fuzzy based intelligent inference algorithm for energy management system with legacy device . The Transactions of the Korean Institute of Electrical Engineers , 2015 , 64 : 779 – 785 .

Cao   T , Hwang   Y , Radermacher   R . Development of an optimization based design framework for microgrid energy systems . Energy , 2017 , 140 : 340 – 351 .

Kanchev   H , Francois   B , Lazarov   V . Unit commitment by dynamic programming for microgrid operational planning optimization and emission reduction. In: International Aegean Conference on Electrical Machines and Power Electronics and Electromotion, Joint Conference , Istanbul, Turkey , 8–10 September 2011 , 502 – 507 .

Tsikalakis   AG , Hatziargyriou   ND . Environmental benefits of distributed generation with and without emissions trading . Energy Policy , 2007 , 35 : 3395 – 3409 .

Moradi   M , Eskandari   M , Showkati   H . A hybrid method for simultaneous optimization of DG capacity and operational strategy in microgrids utilizing renewable energy resources . International Journal of Electrical Power & Energy Systems , 2014 , 56 : 241 – 258 .

Kirthiga   MV , Daniel   SA , Gurunathan   S . A methodology for transforming an existing distribution network into a sustainable autonomous micro-grid . IEEE Transactions on Sustainable Energy , 2012 , 4 : 31 – 41 .

Abou El-Ela   AA , Allam   SM , Shatla   MM . Maximal optimal benefits of distributed generation using genetic algorithms . Electric power systems research , 2010 , 80 : 869 – 877 .

Oudalov   A , Cherkaoui   R , Beguin   A . Sizing and optimal operation of battery energy storage system for peak shaving application. In: 2007 IEEE Lausanne Power Tech 2007 , Lausanne, Switzerland , 1–5 July 2007 , 621 – 625 .

Arefifar   SA , Mohamed   Y . DG mix, reactive sources and energy storage units for optimizing microgrid reliability and supply security . IEEE Transactions on smart grid , 2014 , 5 : 1835 – 1844 .

Luna   R , Perea   M , Vargas-Vázquez   D , et al.    Optimal sizing of renewable hybrids energy systems: a review of methodologies . Solar Energy , 2012 , 86 : 1077 – 1088 .

Iqbal   M , Azam   M , Naeem   M , et al.    Optimization classification, algorithms and tools for renewable energy: a review . Renewable and Sustainable Energy Reviews , 2014 , 39 : 640 – 654 .

Aman   MM , Jasmon   GB , Bakar   AH , Mokhlis   H . A new approach for optimum simultaneous multi-DG distributed generation Units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm . Energy , 2014 , 66 : 202 – 215 .

Schwaegerl   C , Tao   L , Mancarella   P ,   et al . A multi-objective optimization approach for assessment of technical, commercial and environmental performance of microgrids . European Transactions on Electrical Power , 2011 , 21 : 1271 – 1290 .

Boloukat   MH , Foroud   AA . Stochastic-based resource expansion planning for a grid-connected microgrid using interval linear programming . Energy , 2016 , 113 : 776 – 787 .

Zhao   M , Chen   Z , Blaabjerg   F . Optimisation of electrical system for offshore wind farms via genetic algorithm . IET Renewable Power Generation , 2009 , 3 : 205 – 216 .

Lin   N , Zhou   B , Wang   X . Optimal placement of distributed generators in micro-grid. In: 2011 International Conference on Consumer Electronics, Communications and Networks (CECNet) , Xianning, China , 16–18 April 2011 , 4239 – 4242 .

Zhang   D , Evangelisti   S , Lettieri   P , et al.    Economic and environmental scheduling of smart homes with microgrid: DER operation and electrical tasks . Energy Conversion and Management , 2016 , 110 : 113 – 124 .

Dey   B , Roy   SK , Bhattacharyya   B . Solving multi-objective economic emission dispatch of a renewable integrated microgrid using latest bio-inspired algorithms . Engineering Science and Technology, an International Journal , 2019 , 22 : 55 – 66 .

Zhao   B , Zhang   X , Chen   J , et al.    Operation optimization of standalone microgrids considering lifetime characteristics of battery energy storage system . IEEE Transactions on Sustainable Energy , 2013 , 4 : 934 – 943 .

Pourmousavi   SA , Sharma   RK , Asghari   B . A framework for real-time power management of a grid-tied microgrid to extend battery lifetime and reduce cost of energy. In: 2012 IEEE PES Innovative Smart Grid Technologies (ISGT) , Washington, DC, USA , 16–20 Jan. 2012 , 1 – 8 .

Shadmand   MB , Balog   RS . Multi-objective optimization and design of photovoltaic-wind hybrid system for community smart DC microgrid . IEEE Transactions on Smart Grid , 2014 , 5 : 2635 – 2643 .

Zhang   M , Chen   J . The energy management and optimized operation of electric vehicles based on microgrid . IEEE Transactions on Power Delivery , 2014 , 29 : 1427 – 1435 .

Shi   L , Luo   Y , Tu   GY . Bidding strategy of microgrid with consideration of uncertainty for participating in power market . International Journal of Electrical Power & Energy Systems , 2014 , 59 : 1 – 13 .

Alsayed   M , Cacciato   M , Scelba   G ,   et al . Optimal sizing of hybrid power generation systems based on multi criteria decision analysis. In: International Symposium on Power Electronics Power Electronics, Electrical Drives, Automation and Motion , Sorrento, Italy , 20–22 June 2012 , 1442 – 1447 .

Kaabeche   A , Belhamel   M , Ibtiouen   R . Sizing optimization of grid-independent hybrid photovoltaic/wind power generation system . Energy , 2011 , 36 : 1214 – 1222 .

Arnette   A , Zobel   C . An optimization model for regional renewable energy development . Renewable and Sustainable Energy Reviews , 2012 , 16 : 4606 – 4615 .

Alsayed   M , Cacciato   M , Scarcella   G , et al.    Multicriteria optimal sizing of photovoltaic-wind turbine grid connected systems . IEEE Transactions on Energy Conversion , 2013 , 28 : 370 – 379 .

Bahramirad   S , Reder   W , Khodaei   A . Reliability-constrained optimal sizing of energy storage system in a microgrid . IEEE Transactions on Smart Grid , 2012 , 3 : 2056 – 2062 .

Taşcıkaraoğlu   A , Boynuegri   AR , Uzunoglu   M . A demand side management strategy based on forecasting of residential renewable sources: a smart home system in Turkey . Energy and Buildings , 2014 , 80 : 309 – 320 .

Erdinc   O , Paterakis   NG , Pappi   IN ,   et al . A new perspective for sizing of distributed generation and energy storage for smart households under demand response . Applied Energy , 2015 , 143 : 26 – 37 .

Geng   L , Wei   Y , Lu   Z , et al.    A novel model for home energy management system based on Internet of Things. In: 2016 IEEE International Conference on Power and Renewable Energy (ICPRE) , Shanghai, China , 21–23 October 2016 , 474 – 480 .

Lee   JY , Choi   SG . Linear programming based hourly peak load shaving method at home area. In: 16th International Conference on Advanced Communication Technology , Pyeongchang, South Korea , 16–19 February 2014 , 310 – 313 .

Erdinc   O , Paterakis   NG , Catalão   JPS , et al.    Smart households and home energy management systems with innovative sizing of distributed generation and storage for customers. In: 2015 48th Hawaii International Conference on System Sciences , Kauai, HI, USA , 5–8 January 2015 , 1462 – 1471 .

Brahman   F , Honarmand   M , Jadid   S . Optimal electrical and thermal energy management of a residential energy hub, integrating demand response and energy storage system . Energy and Buildings , 2015 , 90 : 65 – 75 .

Asare-Bediako   B , Kling   WL , Ribeiro   PF . Integrated agent-based home energy management system for smart grids applications. In: IEEE PES ISGT Europe 2013 , Lyngby, Denmark , 6–9 October 2013 , 1 – 5 .

Hubert   T , Grijalva   S . Modeling for residential electricity optimization in dynamic pricing environments . IEEE Transactions on Smart Grid , 2012 , 3 : 2224 – 2231 .

Paterakis   NG , Erdinç   O , Bakirtzis   AG , et al.    Optimal household appliances scheduling under day-ahead pricing and load-shaping demand response strategies . IEEE Transactions on Industrial Informatics , 2015 , 11 : 1509 – 1519 .

Wang   J , Sun   Z , Zhou   Y ,   et al . Optimal dispatching model of smart home energy management system. In: IEEE PES Innovative Smart Grid Technologies , Tianjin, China , 21–24 May 2012 , 1 – 5 .

Jo   HC , Kim   S , Joo   SK . Smart heating and air conditioning scheduling method incorporating customer convenience for home energy management system . IEEE Transactions on Consumer Electronics , 2013 , 59 : 316 – 322 .

Rajasekharan   J , Koivunen   V . Optimal energy consumption model for smart grid households with energy storage . IEEE Journal of Selected Topics in Signal Processing , 2014 , 8 : 1154 – 1166 .

Xing   H , Lin   Z , Fu   M . A new decentralized algorithm for optimal load shifting via electric vehicles . In: 2017 36th Chinese Control Conference (CCC) , Dalian, China , 26–28 July 2017 , 10708 – 10713 .

Chen   Z , Xia   B , You   C , et al.    A novel energy management method for series plug-in hybrid electric vehicles . Applied Energy , 2015 , 145 : 172 – 179 .

Wu   X , Hu   X , Teng   Y , et al.    Optimal integration of a hybrid solar-battery power source into smart home nanogrid with plug-in electric vehicle . Journal of Power Sources , 2017 , 363 : 277 – 283 .

Hu   X , Martinez   CM , Yang   Y . Charging, power management, and battery degradation mitigation in plug-in hybrid electric vehicles: a unified cost-optimal approach . Mechanical Systems and Signal Processing , 2017 , 87 : 4 – 16 .

Henao-Muñoz   AC , Saavedra-Montes   AJ , Ramos-Paja   CA . Energy management system for an isolated microgrid with photovoltaic generation . In: 2017 14th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD) , Giardini Naxos, Greece , 12–15 June 2017 , 1 – 4 .

Misra   S , Bera   S , Ojha   T . D2P: distributed dynamic pricing policy in smart grid for PHEVs management . IEEE Transactions on Parallel and Distributed Systems , 2015 , 26 : 702 – 712 .

Setlhaolo   D , Xia   X . Combined residential demand side management strategies with coordination and economic analysis . International Journal of Electrical Power & Energy Systems , 2016 , 79 : 150 – 160 .

Akhavan-Rezai   E , Shaaban   MF , El-Saadany   EF ,   et al . New EMS to incorporate smart parking lots into demand response . IEEE Transactions on Smart Grid , 2016 , 9 : 1376 – 1386 .

Zhang   H , Hu   Z , Xu   Z , et al.    Evaluation of achievable vehicle-to-grid capacity using aggregate PEV model . IEEE Transactions on Power Systems , 2017 , 32 : 784 – 794 .

Su   W , Wang   J , Roh   J . Stochastic energy scheduling in microgrids with intermittent renewable energy resources . IEEE Transactions on Smart Grid , 2014 , 5 : 1876 – 1883 .

Khodakarami   A , Farahani   H , Aghaei   J . Stochastic characterization of electricity energy markets including plug-in electric vehicles . Renewable and Sustainable Energy Reviews , 2017 , 69 : 112 – 122 .

Alipour   M , Zare   K , Abapour   M . MINLP probabilistic scheduling model for demand response programs integrated energy hubs . IEEE Transactions on Industrial Informatics , 2018 , 14 : 79 – 88 .

Klein   L , Kwak   JY , Kavulya   G ,   et al . Coordinating occupant behavior for building energy and comfort management using multi-agent systems . Automation in construction , 2012 , 22 : 525 – 536 .

Megahed   TF , Abdelkader   SM , Zakaria   A . Energy management in zero-energy building using neural network predictive control . IEEE Internet of Things Journal , 2019 , 6 : 5336 – 5344 .

Ruiz-Cortes   M , González-Romera   E , Amaral-Lopes   R , et al.    Optimal charge/discharge scheduling of batteries in microgrids of prosumers . IEEE Transactions on Energy Conversion , 2018 , 34 : 468 – 477 .

Elsied   M , Oukaour   A , Youssef   T ,   et al . An advanced real time energy management system for microgrids . Energy , 2016 , 114 : 742 – 752 .

Radosavljević   J , Jevtić   M , Klimenta   D . Energy and operation management of a microgrid using particle swarm optimization . Engineering Optimization , 2016 , 48 : 811 – 830 .

Marzband   M , Ghazimirsaeid   SS , Uppal   H ,   et al . A real-time evaluation of energy management systems for smart hybrid home microgrids . Electric Power Systems Research , 2017 , 143 : 624 – 633 .

Sousa   T , Morais   H , Vale   Z , et al.    Intelligent energy resource management considering vehicle-to-grid: a simulated annealing approach . IEEE Transactions on Smart Grid , 2012 , 3 : 535 – 542 .

Chaouachi   A , Kamel   RM , Andoulsi   R , et al.    Multiobjective intelligent energy management for a microgrid . IEEE Transactions on Industrial Electronics , 2013 , 60 : 1688 – 1699 .

Solanki   BV , Bhattacharya   K , Cañizares   CA . A sustainable energy management system for isolated microgrids . IEEE Transactions on Sustainable Energy , 2017 , 8 : 1507 – 1517 .

Guo   Y , Zhao   C . Islanding-aware robust energy management for microgrids . IEEE Transactions on Smart Grid , 2018 , 9 : 1301 – 1309 .

Viciana   E , Alcayde   A , Montoya   FG ,   et al . An open hardware design for Internet of Things power quality and energy saving solutions . Sensors , 2019 , 19 : 627 .

Bollen   M , Zhong   J , Zavoda   F ,   et al . Power Quality aspects of smart grids. In: International Conference on Renewable Energies and Power Quality (ICREPQ’10) , Granada, Spain , 23–25 March 2010 , 1 – 6 .

Hartono   BS , Mursid   SP , Prajogo   S . Home energy management system in a Smart Grid scheme to improve reliability of power systems . IOP Conference Series: Earth and Environmental Science , 2018 , 105 : 012081 .

Nguyen   DT , Le   LB . Risk-constrained profit   maximization for microgrid aggregators with demand response . IEEE Transactions on smart grid , 2014 , 6 : 135 – 146 .

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Smart Home: Definition, How They Work, Pros and Cons

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and behavioral finance. Adam received his master's in economics from The New School for Social Research and his Ph.D. from the University of Wisconsin-Madison in sociology. He is a CFA charterholder as well as holding FINRA Series 7, 55 & 63 licenses. He currently researches and teaches economic sociology and the social studies of finance at the Hebrew University in Jerusalem.

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A smart home refers to a convenient home setup where appliances and devices can be automatically controlled remotely from anywhere with an internet connection using a mobile or other networked device.

A smart home refers to a convenient home setup where appliances and devices can be controlled automatically or remotely with an internet connection and using a mobile or other networked device.

Devices in a smart home are interconnected through the internet, allowing the user to control functions such as security, access to the home, temperature, lighting, and a home theater.

Key Takeaways

• A smart home allows homeowners to control appliances, thermostats, lights, and other devices remotely through an internet connection using a smartphone or tablet.
• Smart homes can be set up with wireless or hardwired systems.
• Smart home technology provides homeowners with convenience and cost savings.
• Security risks and bugs continue to plague makers and users of smart home technology.
• Though full-scale home automation may cost thousands of dollars, smaller individual products can cost less than $100.

How Smart Homes Work

A smart home’s devices are connected with each other and can be accessed through one central point—a smartphone , tablet, laptop, or game console. Door locks, televisions, thermostats, home monitors, cameras, lights, and appliances such as the refrigerator can be controlled through one home automation system.

The system is installed on a mobile or other networked device, and the user can schedule the performance of tasks and devices.

Smart home appliances come with self-learning skills. They can learn the homeowner’s schedules and make adjustments as needed. Smart homes enabled with lighting control allow homeowners to reduce electricity use and benefit from energy-related cost savings.

Some home automation systems alert the homeowner if any motion is detected in the home when they're away. Others can call the authorities—the police or the fire department—if dangerous situations arise.

Once connected, services such as a smart doorbell, smart security system, and smart appliances become part of the internet of things (IoT) technology, a network of physical objects that can gather and share electronic information.

Security and efficiency are the main reasons for the increase in smart home technology use.

Smart homes can feature either wireless or hardwired systems—or both. Wireless systems are easier to install. Putting in a wireless home automation system with features such as smart lighting, climate control, and security can be limited in cost to several thousand dollars, making it relatively cost-friendly.

The downside to wireless systems is you likely need strong Wi-Fi coverage and broadband service throughout your entire house. This may require you to invest in range extenders or hardwired wireless access points. Wireless smart home systems are generally more appropriate for smaller existing homes or rental properties.

Hardwired systems, on the other hand, are considered more reliable. They are typically more difficult to hack. A hardwired system can increase the resale value of a home. In addition, hardwired smart home systems can be scaled easily. Therefore, it is often the default method when designing a new build or performing a major renovation.

There is a drawback—it's fairly expensive. Installing a luxury and hardwired smart system can cost homeowners tens of thousands of dollars. In addition, you must have space for network hardware equipment including Ethernet cables.

Components of a Smart Home

Smart home products now allow for greater control over heating devices, including turning products on and off, and controlling settings. Smart products may be armed with temperature or humidity sensors to automatically turn on or off if certain criteria are met. This line of smart home innovations also extends to air conditioners.

Often with the use of a mobile phone, tablet, or custom remote specific to a product, lighting products now offer homeowners enhanced capabilities and convenience. Lights can be switched on and off, placed on a schedule, or set to change based on sunrise or sunset times. Like some more traditional products, lights can often be set to change based on motion. Smart bulbs can communicate over Wi-Fi and display statistics or metrics on your phone.

This lighting category may also contain smart home products that control the degree of light. Automatic blinds may be installed and set to close based on sunrise schedules. Alternatively, electronic curtains allow users to manage their blinds using a handheld device.

Audio/Visual

One of the more appealing aspects of smart homes is the many entertainment products that can be connected to each other and controlled with a single remote. Television and speakers can be played on command using applications. They can be operated according to a schedule or by voice-control.

One of the most important aspects of a smart home is the enhanced security capabilities it offers. Products with cameras track motion, capture video, or allow for live video feeds. These may be installed to sync with a ringing doorbell or set to capture certain areas of your property. Products can facilitate audio as well as video calls with individuals at your door.

Many smart homes are also refit with advanced security kits. These kits includes motion sensor detectors, home monitoring, notifications and alerts concerning suspicious behavior, and the ability to lock doors or windows remotely using a phone.

Smart homes can also include digital assistants or home hubs. People interact with these products using their voice and by issuing commands. They can field questions, organize your calendar, schedule conference calls , or provide alerts.

Smart smoke and carbon monoxide detectors not only sound an alarm but can be synced to your phone to alert you should you be away from your property. These devices can often be set up to send emergency notifications to other, specified contacts.

People have been able to program automated irrigation systems for a while. Now, smart irrigation systems can detect climate and environmental conditions and factor them into watering schedules. Smart irrigation systems can also monitor moisture-related conditions and control irrigation to conserve water.

When budgeting for smart home products, remember to consider the costs related to necessary labor/installation work.

Advantages and Disadvantages of Smart Homes

• Smart home technology systems offer homeowners convenience. Rather than controlling appliances, thermostats, lighting, and other features individually themselves or by using different devices, homeowners can control them all using one device—usually a smartphone or tablet.
• Security may be enhanced because users can get notifications and updates on issues in their homes when they're away. For instance, smart doorbells allow homeowners to see and communicate with people who come to their doors when they're not at home.
• Despite the cost of installing a smart system, homeowners can benefit from significant cost savings over time. Appliances and electronics can be used more efficiently, lowering energy costs.

Disadvantages

• Security risks and bugs continue to plague makers and users of smart home technology. Adept hackers, for example, can gain access to a smart home's internet-enabled appliances. For example, in October 2016, a botnet called Mirai infiltrated interconnected devices of DVRs, cameras, and routers to bring down major websites through a denial of service attack , also known as a DDoS attack.
• Risk mitigation involves the added effort of maintaining and periodically changing strong passwords, using encryption when available, and only connecting trusted devices to one's network.
• The costs of installing smart technology can run anywhere from a few thousand dollars for a wireless system to tens of thousands of dollars for a hardwired system.
• Learning to use the home system may involve a steep learning curve.

Smart Homes

Are often more convenient than traditional methods of scheduling, controlling, or accessing products

May enhance security due to notifications or alerts

Offers multiple ways of performing a certain task (e.g., lights can be turned on manually, automatically, remotely)

May result in long-term cost savings due to efficient energy consumption

May pose security risk as products are connected to networks that can be hacked

May require additional work for homeowner related to tracking additional passwords and monitoring product security

Are often more expensive than their less- or non-smart counterparts

May involve a steep learning curve, especially for those not tech-savvy

According to HomeAdvisor, it may cost up to $15,000 to fully automate an average four-bedroom, three-bath home. Fully-connected luxury homes may run into the six figures.

Home Much Does a Smart Home Cost?

As more and more smart home products are brought to market, pressure to lower prices will be put on manufacturers and their competition. On the other hand, innovations are continually expanding what smart home products can do. As a result, prices for the latest technology may remain high.

When contemplating smart home products, consider performing a cost-benefit analysis to determine whether the product price exceeds the benefits it offers you.

In general, you can start by focusing on a specific product or room. This strategy allows individuals to invest in smart technology for minimal capital. Consider the following options priced at less than $100 as of April 2024:

• Google Nest Mini, the home audio and assistant device
• Amazon Smart Plug, a method of automating appliances
• Ring Smart Doorbell, a video-enabled camera for home security
• Wyze Thermostat, a digital, wireless, programmable heating device

What Is In a Smart Home?

Smart homes can have smart speakers, lights, thermostats, doorbells, or home hubs. Smart technology can also extend to kitchen appliances and outdoor or landscaping equipment. New innovations are continually evolving what is in a smart home.

Why Is a Smart Home Important?

A smart home is important because it allows a household to become more energy efficient. In addition, it allows people to save time and perform tasks more easily and efficiently. A smart home also offers a level of convenience that's absent with the manual method of performing tasks (e.g., turning on lights yourself).

Can a Smart Home Be Hacked?

Yes. Because smart home systems often require a live network connection, they can be hacked if the security protocol is inadequate. In addition, individuals must be careful about sharing sensitive login information, such as passwords.

Is a Smart Home Worth It?

It can be. You must do the research to determine whether the potential convenience, added security, and cost savings over time outweigh the cost to install a full home system. Consider using individual smart home products first to learn how well they fit your lifestyle and budget.

Leveraging innovation and technology, smart homes simplify the daily tasks faced by homeowners and add new capabilities that may enhance their security. The smart home will continue to evolve.

Whether you control home products remotely using your phone or schedule the performance of tasks for certain times, smart homes have revolutionized the way people control the products they live with.

Stolojescu-Crisan, Cristina and et al. " An IoT-Based Smart Home Automation System ." Sensors (Basel) , vol. 21, no. 11, June 2021.

Setayeshfar, Omid and et al. " Privacy Invasion via Smart-Home Hub in Personal Area Networks ." Pervasive and Mobile Computing , vol. 85, September 2022.

Antonakakis, Manos and et al. " Understanding the Mirai Botnet ." Proceedings of the 26th USENIX Security Symposium, August 2017, pp. 1093-1110.

HomeAdvisor. " How Much Does a Smart Home Cost? " Scroll down.

Google. " Nest Mini ."

Amazon. " Amazon Smart Plug | Works with Alexa ."

Ring. " Battery Doorbell Pro ."

Wyze. " Wyze Thermostat ."

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Advantages and Disadvantages of a Smart Home

By benny kounlavouth ,.

When you buy through our links, we may earn an affiliate commission.

More and more families across the world are adopting smart home technology into their homes and daily routines. 

In my opinion, a smart home has many advantages and few disadvantages. But, every family is different. 

Pros & Cons of Smart Home Technology

Smart devices add a lot of value to my daily routine and really help me be more efficient. For that reason, I do believe smart home technology is worth it. 

But technology moves fast, and keeping up with the latest and greatest can be a struggle. Plus, the initial costs and internet reliance makes smart homes unfeasible for some.

There’s no perfect answer — it’s up to you to weigh the pros and cons and decide what’ll work best for your family.

Advantages of a Smart Home

Remote control.

Most smart home devices connect to the internet, either directly or through a hub. This means you can access those devices from anywhere you have an internet connection.

Here are some examples of how remote control can make your life easier:

• You just got to work but forgot to turn off a few lights around the house. Turn them off with your smart bulb or switch app .
• Someone is at your door, but you aren’t home. See and speak to the visitor through your smart doorbell’s app .
• You normally lower the heat when you go to work, but you forgot today. Smart thermostats allow you to control the temperature from anywhere .

We could probably fill a book of examples, but these three cases give you an idea of the possibilities.

Energy Saving & Monitoring

From energy monitoring to lowering the temperature of your home while you’re away, smart home devices help you keep track of how much energy you’re actually using. 

Smart plugs can give you energy consumption reports , and some even have controls that automatically turn a socket off when a device has consumed a certain amount of energy.

Smart thermostats can learn your schedule and heating and cooling preferences , then automatically adjust to keep your home running as efficiently as possible. 

Customization

Smart homes can be as complex or simple as you choose. There really is no “one-size-fits-all” solution. Whether you want to take advantage of one device or twenty is completely up to you .

Home automation is adaptable depending on: 

• Whether you rent or own your home
• How much of your home you want to automate
• How much y ou want to spend

There are literally hundreds, if not thousands, of devices. You can automate almost every aspect of your home, or just a couple of rooms . 

Pick one, pick two, pick them all! You have options in each category and they’re all useful in their own way.

Convenience

Smart home technology allows your home to run more efficiently and work better for you. It is up to you to find the devices that will improve your life and add value to your home.

You can always be home to greet your visitors with a smart video doorbell. You can have your door automatically unlock when you arrive home from work. You can even use your voice to turn on lights or start a pot of coffee.

There is an added level of safety that comes with smart devices. Door, window, and motion sensors alert you when movement is detected in your home , and depending on what you have connected, could even send a livestream to your phone. 

There are even smart smoke detectors and CO2 sensors . These work similarly to their “dumb” counterparts, but with the bonus of sending a notification to your phone when smoke or CO2 is detected in your home.

Google Nest’s smart smoke detector will even tell you exactly where the problem is through built-in speakers.

(Alarm Sound) “Emergency. There’s carbon monoxide in the (room name). Move to fresh air.”

-Google Nest Protect warning message

Video doorbells and smart security cameras also add a layer of protection. They allow you to see anyone in or around your home from anywhere and can record whenever they sense motion .

Voice Commands & Routines

Another benefit of smart home technology is hands-free control and setting routines. A routine is an action that sets off other actions within your connected home.

You can set up routines to trigger: 

• When you say a certain phrase
• At a certain time of the day
• On designated days  

These routines can include anything from turning smart devices on and off to getting news briefs or weather reports.

For example, my morning routine is triggered by the phrase “ Alexa, good morning .” That command turns on my lights, tells me the weather, goes through the news brief, and starts a pot of coffee.

Check out this video of a completely hands-free home, controlled by voice commands and Alexa Routines.

Accessibility

There are many smart devices you can control using just your voice, making smart home technology a wonderful tool for the differently-abled. 

Here are just a few of the ways smart tech can make life at home more accessible :

• Smart switches and bulbs let you turn lights on or off without flipping a switch.
• Smart video doorbells let you see and talk to anyone at the door from your phone.
• Smart assistants can help you make phone calls or send text messages when you aren’t near the phone. 

Whether you have limited mobility or want to make life easier for an older relative, smart home technology can make doing things around the house much simpler.

It Can Increase Your Home’s Value

Smart technology and devices can also increase your home’s value . If you plan to sell anytime soon, those permanent smart fixtures will attract more buyers and may even shorten the time it takes to sell your home.

In addition, many insurance companies are willing to offer policy discounts for homes with certain smart devices. Some of the smart devices that may quality include:

• Smart security systems
• Smart security cameras
• Smart water sensors

Disadvantages of a Smart Home

Perhaps the biggest disadvantage of smart technology is the price. While the initial costs of individual products usually aren’t too bad, continually adding more products can get expensive fast . 

Installing smart cameras, sensors, and lights is pretty simple, and you can usually do it on your own. But when you get into big-ticket items like smart thermostats and kitchen appliances, which may require professional installation, the costs begin to add up. 

Before you add any smart device to your home, big or small, weigh the cost-saving benefits vs. your total investment to ensure you’re making the right decision.

Compatibility Issues

If you want a fully-automated home, you’ll need to make sure each device you purchase is compatible with what you already own.

Let’s say you prefer Google Assistant over Amazon Alexa. Both devices work similarly, so you don’t see any issue choosing one over the other. 

But then you decide to add a Ring Video Doorbell to your smart home. Great device, only one problem — it’s not compatible with Google Home . 

While there’s nothing wrong with using incompatible devices across your smart home, it complicates the process . If you’re choosing a smart home because of convenience, you’ll need to do your research and find the right products . 

Smart home technology is a bit of a double-edged sword when it comes to security. While it does make our homes more secure in many ways, it can also make it less secure in others.  

It goes without saying that connecting anything to Wi-Fi comes with some sort of security risk, and while it’s usually low, there’s always the potential for your tech to get hacked .

Is Alexa recording what you say ? Can someone hack your Ring account and watch you in your home ? As long as you take the right steps to secure your accounts and use a strong password , you probably have nothing to worry about. 

But, the risk alone is enough to turn some people off of smart technology.  

Companies Can Fail

The worst thing that can happen with your smart device is that the company that makes it goes out of business. While it’s rare, it does happen from time to time . If they take their servers down, your product basically becomes unusable. 

Technology moves fast, and some companies just aren’t built for the competition. Try to go with reputable, tried-and-true brands whenever you can to minimize the risk.

Adapting Smart Tech into Your Daily Routine

Adapting to anything new takes a little time. 

If you’re a tech-savvy person, you should catch on pretty quickly. But it might not be the best idea to introduce your grandmother, who still uses a rotary phone, to the Echo Dot , Ring, Philips Hue smart bulbs , and an ecobee thermostat all at the same time. 

It takes a little time to adjust, but it does get easier for users to control their smart homes with time and practice. Once you form that habit, it’s hard to imagine life without smart technology !

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This Video Doorbell Has Everything I Want, Without the Monthly Fees

I love this quick and dirty light automation toggle for apple home, i never thought i'd need a smart clock, but here's why i love it.

You've probably heard the term "smart home" a lot recently. But what exactly is a smart home? What makes it "smart" and why would someone be interested in converting their home?

We're going to walk you through the ins and outs of a smart home so that you know whether the technology is for you.

What Is a Smart Home?

A smart home is any home that uses some form of electronic device to control or automate everyday tasks. These homes often consolidate around a central hub that allows communication between all of the devices located in the house.

These devices can range from temperature sensors, smart thermostats, wall switches, smart plugs, water sensors, door and window sensors, motion sensors, and many other integrated devices. Like your smartphone—which does more than just allow you to make phone calls—a smart home can allow you to automate many of your home tasks.

For example, let's say you wanted to have your thermostat automatically decrease the temperature when you left for work in the morning. A smart home with an integrated thermostat could allow you to do that. Or, if you wanted to unlock your front door for guests, but you were stuck at the office, a well-equipped smart home would allow you to.

Finally, what if you wanted to turn off your Christmas lights at precisely 9 p.m. on Saturday and Sunday? A smart home with the proper setup could also allow you to automate this task. Some smart home devices can even vacuum your house or mow your lawn.

Smart homes save time, increase security, improve comfort, and make life more enjoyable for homeowners.

Related: What is a Smart Home Hub?

How Do Smart Homes Work?

The easiest way to describe how a smart home works is to think of the home like the human body. In most smart homes, there is a brain, which is often an app or a set of apps on a mobile device. This central device is known as a hub.

The hub directs all activity to the smart devices on the network. If the home is like a body, these devices are its limbs. Using the power of the internet and integrated connectivity, these devices get instructions from the hub and then perform certain mechanical behaviors based on those instructions.

The behaviors—called automations—can range from sending a text to a family member to turning on all of the lights in the house and engaging a security alarm.

Many people have built smart homes that perform complex tasks, and companies like Apple and SmartThings have included programming tools in their software to make creating these automations easier.

Related: The Best Smart Doorbells for Your Home

Smart Home Communication Protocols

To communicate with devices, smart home hubs need some sort of communication language that both the device and the hub understand. Because many smart home products exist on the market, several manufacturers have standardized these communication protocols. Rather than using several hundred protocols that don't work together, the smart home industry has narrowed it down to just a few: Zigbee, Z-Wave, Thread, KNX, Control4, Bluetooth, and Wi-Fi.

The most prominent protocols currently in use are Zigbee and Z-Wave. However, many manufacturers have begun to move more toward Thread as it offers some unique benefits over the other, more popular, protocols. Additionally, some Bluetooth devices don't need internet connectivity to function, which appeals to some people.

Related: What's the Difference Between Zigbee and Z-Wave?

Smart Home Benefits

What are some of the most significant benefits of a smart home? The most considerable benefit is convenience. Smart homes allow you to do things like control HVAC in your home from anywhere in the world (including your couch), turn lighting on or off, control external sprinkler systems, and even view guests arriving at your front door.

Most of these tasks can be completed using a mobile device or the smart home hub. You can even set up certain tasks to happen at specific times or on particular days. Setting a smart thermostat optimally or setting an irrigation system to stay off when it's raining are ways that smart homes can also save money.

Smart homes can also eliminate some of the hassles of access that plague some homeowners. If you have a dog-walker or a landscaping service, you can give those people access to your home even if you are away at work or on vacation.

Customization is also a significant benefit of smart homes. Because there are so many products available, you can tailor your home to your personal preference. Every smart home is as unique as its owner, and the possibilities are only as limited as your imagination.

Lastly, smart homes offer upgraded security benefits over a typical home. In-home cameras and doorbell cameras can make thieves think twice about trying to break in. Motion sensors and door/window sensors can also keep rambunctious teenagers from leaving the house without you knowing about it.

Smart Home Downsides

There are only a few minor issues that can come up with a smart home, and they all have to do with connectivity.

When a device malfunctions or loses its connection, it can create havoc. Because networks fail frequently, you may want to consider what alternative methods of control you have if a smart item stops working. Fortunately, these connectivity issues are usually only temporary.

Related: How to Reconnect a Smart Light Switch That Has Lost Connection

Getting Started With Your Smart Home

There are some great products available if you are interested in setting up a smart home. Though, it's best to plan out your installation before you go buying random tech. For many people, a smart home starter kit is an excellent place to begin the journey. These kits offer many standard devices, such as motion sensors and smart plugs, that you can experiment with before diving in deep.

You might also want to check out some of the most common products, such as smart bulbs or thermostats. Also, there are many uses for inexpensive smart plugs to get your creativity started. It's recommended that you brainstorm some ideas about how you might use these items before buying, though, just to make sure you're not wasting your money.

A Smarter Home Starts Here

Building your own smart home doesn't have to be complicated or expensive. Adding a few products at first and doing some experimentation can open the door to a home that offers much higher levels of convenience and comfort. By building a smart home, you're upgrading your security, customization, flexibility, and satisfaction.

You also don't need to buy a lot of products to consider your home smart. One or two is enough. Just know, if you really want to customize your space to its fullest potential, then the option is also available.

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What Will Smart Homes Look Like 10 Years From Now?

I t’s 6 A.M., and the alarm clock is buzzing earlier than usual. It’s not a malfunction: the smart clock scanned your schedule and adjusted because you’ve got that big presentation first thing in the morning. Your shower automatically turns on and warms to your preferred 103°F. The electric car is ready to go, charged by the solar panels or wind turbine on your roof. When you get home later, there’s an unexpected package waiting, delivered by drone. You open it to find cold medicine. Turns out, health sensors embedded in your bathroom detected signs of an impending illness and placed an order automatically. Good thing you already knocked that presentation out of the park.

That, at least, is the utopian version of the smart home that exists 10 years out. Swedish research firm Berg Insight says 63 million American homes will qualify as “smart” by 2022, with everything from Internet-connected light bulbs to cameras that let us spy on our pets from the office (there were nearly 130 million homes in the U.S. in total in 2018). But a decade from now, experts say, we’ll move from turning the lights on and off with our voices to total immersion in the Internet of Things (IoT). Thanks to advancements in artificial intelligence, the smartest homes will be able to truly learn about their owners or occupants, eventually anticipating their needs. Developments in robotics will give us machines that offer a helping hand with cleaning, cooking and more. New sensors will keep tabs on our well-being. Central to all of this will be the data that smart homes collect, analyze and act upon, helping to turn the houses of the future from a mere collection of gadgets and accessories into truly “smart” homes.

All the automated attentiveness will come with a high price tag: consumers will spend $123 billion on IoT gear by 2021, according to advisory firm ABI Research, a number that’s likely to rise thereafter. Aside from Internet-connected televisions, manufacturers are putting their R&D and marketing budgets behind home-monitoring and security gadgets–they will have 22.6% of the smart-home market share by 2023, estimates research firm IDC, with smart speakers and lighting equipment not far behind, at 15.4% and 11.8% respectively. There are already at least 7 billion connected IoT devices, according to market-research company IoT Analytics. But as smart-home technology becomes easier to use and its benefits become more clear, the industry is poised to take off. “Sustained growth is expected to continue … as consumers adopt multiple devices within their homes and as global availability of products and services increases,” according to IDC.

Of course, as our homes learn more about us, keeping them secure will become all the more important. Every device that’s connected to the Internet is a potential target for hackers. When we’re talking about devices that can unlock our homes from afar, peer into our living rooms using cameras, and collect our most sensitive and personal data, cybersecurity will become all the more vital. Any kind of massive breach that turns off consumers, says Daniel Cooley, chief strategy officer at electronics-component manufacturer Silicon Labs, could be catastrophic for the industry. “I call it a mass-extinction event for the Internet of Things,” he says.

A range of technological developments will drive smart-home technology well beyond what’s available on store shelves today. Innovations in artificial intelligence, for example, stand to upend almost everything in our lives, including our homes. You might already be using some kind of AI-powered voice-assistant gadget to get the latest news or weather forecast every morning. But in the smart home of the future, those AI platforms could serve as the brain for entire homes, learning about residents and coordinating and automating all of their various smart gadgets. IoT company Crestron, for example, is working on software that tracks a person’s habits, like which music they want to hear in the morning or which lights they want to be on at a certain time of day. Then, once it gets the hang of a user’s preferences, it automatically plays just the right playlists or dims the lights before bedtime. “That’s really the next evolutionary step in true automation,” says John Clancy, head of Crestron’s residential business.

Robots, too, will have a role to play in the smart home of the future. Smart vacuum cleaners like iRobot’s Roomba are already picking up after us, while products like the Aibo, a robotic dog for children, show how they might help keep us company like a pet. As for the future? Robotic-furniture company Ori Living is working with Ikea on pieces that change based on your needs, getting the bed out of the way when you need a desk, or hiding your closet when it’s dinnertime. Design firm Design3 recently showed off a smart-home robot concept, CARL. The fabric-covered bot is meant to slowly roll around your home, activating its retractable cameras and sensors to detect intruders, notify you of any harmful emissions or keep an eye on your pet. And computer-graphics company Nvidia is working on a smart robotic arm that can act as its owner’s personal sous chef, doing everything from slicing and dicing veggies to helping with cleanup; it could be particularly useful for busy parents or disabled users. If such a device went into production, cameras and sensors could help prevent it from accidentally injuring an innocent bystander who’s just on the way to the fridge for a quick snack before dinnertime.

Health applications will drive at least some of the smart-home growth over the next decade. Cameras and sensors embedded in refrigerators will suggest more nutritious alternatives if people are reaching for the sugary sodas a little too frequently. Similar technology in medicine cabinets will check if residents have taken their prescriptions. And sensors will even show up in toilets to check for signs of any potential health conditions by scanning human waste before it’s flushed. Bathroom-fixture company Toto has experimented with urine-sampling toilets, while one company has filed patents for devices including a mirror that’s meant to monitor users’ health just by analyzing their skin. Homes will have health sensors of their own, too, that check for issues like water damage, pest infestation and so on, alerting owners to any potential problems before they become far costlier to manage.

All this learning and scanning that the smart home of the future will be doing may understandably raise privacy concerns. Indeed, some smart-home devices have already been targeted by hackers, whether to access the data they hold or to use them as tools in larger cybersecurity schemes. In 2016, hackers took over hundreds of thousands of insecure IoT devices, then used them to send bogus Internet traffic to target websites in hopes of crashing them; the incident temporarily crippled Internet connections throughout parts of North America and Europe. Government regulation is in the works too. A bill put forth by Virginia Senator Mark Warner in March would push the government to set up minimum security requirements for smart devices used by federal agencies; such requirements could eventually become standard for the industry at large.

You’re more likely than not to end up in a connected home one day, whether you mean to or not. Architect Michael Gardner, founder of construction firm Luxus Design Build, says homes are increasingly being built “smart” from the ground up. “It’s such an integral part of the home that we’re designing it from the beginning, where beforehand technology was always an afterthought,” he says. Ultimately, experts say, people will come to see smart-home technology as essential as electricity, refrigeration or air-conditioning. Smart-home tech, and the data it collects, will “be like plumbing,” says Cooley, from electronics-component manufacturer Silicon Labs. “You’ll rely on it.”

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• Published: 21 February 2020

Social impacts and control in the smart home

• Larissa Nicholls   ORCID: orcid.org/0000-0001-6841-0696 1 ,
• Yolande Strengers 1 &
• Jathan Sadowski 1  

Nature Energy volume  5 ,  pages 180–182 ( 2020 ) Cite this article

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The smart home technology industry promises energy savings and lifestyle improvements. However, there is little evidence that smart home technologies will reduce home energy use overall, and there are a range of emerging detrimental social impacts that require further attention from researchers, policymakers and practitioners.

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Energy 2020 - A Strategy For Competitive, Sustainable And Secure Energ y (European Commission, 2010).

Bernheim Brush, A. J. et al. Home automation in the wild: challenges and opportunities. In Proc. SIGCHI Conference on Human Factors in Computing Systems 2115–2124 (ACM, 2011).

D’Arcy, J. TechKnow: Get smart to turn on the aircon and check the power usage. The Sydney Morning Herald (14 September 2015).

Strengers, Y., Pink, S. & Nicholls, L. Energy Res. Soc. Sci. 48 , 108–115 (2019).

Article   Google Scholar  

Hargreaves, W., Wilson, C. & Hauxwell-Baldwin, R. Build. Res. Inf. 46 , 127–139 (2018).

The Strategic Energy Technology (SET) Plan (European Commission, 2017).

Nicholls, L., Strengers, Y. & Tirado, S. Smart Home Control: Exploring the Potential for Off-The-Shelf Enabling Technologies in Energy Vulnerable and Other Households (RMIT University, 2017).

Tuohy, J. What can I do with home automation? Network World https://www.networkworld.com/article/2874954/what-can-i-do-with-home-automation.html (2015).

Tuohy, J. What is home automation and how do I get started? Network World https://www.networkworld.com/article/2874914/what-is-home-automation-and-how-do-i-get-started.html (2015).

Strengers, Y. & Nicholls, L. Media Int. Aust. 166 , 70–80 (2017).

Strengers, Y. Smart Energy Technologies in Everyday Life Smart Utopia? (Palgrave Macmillan, 2013).

Strengers, Y., Kennedy, J., Arcari, P., Nicholls, L. & Gregg, M. Protection, productivity and pleasure in the smart home: emerging expectations and gendered insights from Australian early adopters. In Proc. 2019 CHI Conference on Human Factors in Computing Systems 1–13 (ACM, 2019).

Hargreaves, T. & Middlemiss, L. Nat. Energy https://doi.org/10.1038/s41560-020-0574-0 (2020).

I’d Blush If I Could: Closing Gender Divides in Digital Skills Through Education (UNESCO for the EQUALS Skills Coalition, 2019).

Lopez-Neira, I., Patel, T., Parkin, S., Danezis, G. & Tanczer, L. The Domestic Abuse Quarterly 63 , 22–26 (2019).

Google Scholar  

Tech Abuse: Smart Internet-Connected Devices Present New Risks for Victims of Domestic Violence & Abuse (UCL Public Policy, 2018).

Phair, N. Smart Meters: What Does A Connected House Really Mean? (University of Canberra, 2017).

Strengers, Y., Hazas, M., Nicholls, L., Kjeldskov, J. & Skov, M. B. Int. J. Hum-Comput. St . https://doi.org/10.1016/j.ijhcs.2019.102379 (2020).

Maalsen, S. & Sadowski, J. Surveill. Soc. 17 , 118–124 (2019).

Keep your family on schedule with smart lighting. UKnowKids https://resources.uknowkids.com/blog/keep-your-family-on-schedule-with-smart-lighting (2015).

Boehnert, J. & Mair, S. Techno-fix futures will only accelerate climate chaos – don’t believe the hype. The Conversation https://theconversation.com/techno-fix-futures-will-only-accelerate-climate-chaos-dont-believe-the-hype-125678 (2019).

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Smart House System Technology Explained

Introduction, energy management, security system, lighting system, smart appliances, entertainment, emergency management.

Smart House is a term used to describe a house that has Computer Controlled Automation System that controls various functions in a house such as appliances and lighting. This system employs smart technology allowing for networking of appliances hence enabling access and operation of the appliances from any part of the network. The system can be used in monitoring, warning and carrying out various functions according to selected criteria. The smart technology enables automatic communication via the mobiles phones, the internet and the fixed telephones.

Smart technology makes use of different electronics components, performing different functions. These components are divided into the following general groups:

• Sensors: for monitoring and submitting any changes, examples are humidity sensor, smoke detectors, movement and heat sensors, thermometers etc.
• Actuators: These components perform physical actions; examples are automatic light switches, relays and door and window openers.
• Controllers: these components make choice based on occurrences and programmed rules.
• Central units: Used in programming and making changes to a system, a good example is a computer.
• Interface: These are components which help user to communicate with the system.

The most important aspects to be taken care of for a house to be considered smart are:

• Energy management
• Emergency management
• Smart appliances.

Smart houses are considered very efficient in energy management.Electronics devices are installed in the house to monitor the usage of the energy and the number of people in the house at a particular time for energy regulation. When there is no one in the house, the temperatures settings are lowered automatically and all the appliances and lights that are not in use are turned off. The energy management system also controls heating system, fans and air conditioners in a way that will save energy. The smart house energy system also automatically turns off energy from an outlet that is not being used.

Smart house energy management system helps in saving energy cost by up to 65% compared to a house where energy usage is controlled manually.

A smart house is far much secure as it is easy to protect making it hard to break in than the current house. Alarm systems, similar in application to car alarm are installed in a smart house. The security system put the house in security mode, automatically shutting all windows and doors.

The smart house security system is programmed for a single day use or for a long time when the owner of the house is in a long trip or vacation. In this case, the security system is set to open the curtains and turn on and off the lights, making it look like there is a person in the house.

As part of the security system, surveillance cameras are installed and hidden around the house. These camera are monitored over the internet and the house owner can check at all aspects of the house include burglars and other unusual happening around and inside the house.

Smart house employs lighting system that makes the house safe and easier to live in by use of programmable lights or remotely accessed lighting system. With programmable lighting system, the house owner programs the lights to come on of off at a specific time and even dim depending with the mood. A central computer is used to turn specific lights at a specific time during the night. This helps in deterring criminals, hence improving security. With remote access, lights can be controlled remotely from any where inside or outside the house using mobile phones or PDAs.

For a house to be considered smart, smart appliances are installed to make use of the smart technology. The appliances are networked in the system to perform specific task at a given time.

Examples of smart appliances include remote controlled coffee maker which brews coffee just before the house owner wakes up. The coffee maker is linked to an alarm to wake up the house owner when the coffee is ready. A smart refrigerator automatically adjusts the temperatures inside based on the temperature of food inside. These smart appliances are connected to a computer which automatically turns the appliances on and off.

Smart appliances make the life of people calmer and better structured as the technology make planning of the day easier. This tranquility help people to concentrate on a specific task as other tasks are being carried on without a lot of monitoring and intervention.

Smart entertainment systems are designed to controls the way home entertainment system including the TV and Home theatre system functions. Smart TV user have the ability to change channels by either speaking or accessing the TV via the internet, instructing it on what to record and at what time. Ultra Thin rear projections TVs have been developed using Digital Light Technology (DLP), they have massive screen sizes, and they are slim and light enough to hang on the wall.

Smart internet enabled home theatres system stream music from multiple computers on the internet and store in an internal hard drives. This home theatre can be accessed remotely over the internet to control almost all aspects of the system.

A smart house emergency system is designed in a way that it will inform house occupant where there is an emergency and at the same time contact the relevant authority on the emergency for a quick response. If there is fire for example, the fire detector sends a signal to the central computer which triggers the alarm and at the same time make a call to the fire department.

Another example is when there is a gas leakage in the house; the emergency control system will shut down the main gas supply and turn off all electrical appliances to prevent any fire out break. The system will then turn on the alarm and send a signal to the house owner informing them on the gas leak though the mobile phone or through the internet to a personal computer.

Smart houses are the choice for most people as they improve the lives of people in a great way making it easier to live because of the convenience and safety they offer. With automatic smart appliances, people are able to plan their time and concentrate on important tasks in their lives.

Chris D. Nugent (2006) Smart Home and Beyond, IOS Publishers, United States.

David Heckman (2008) A Small World: Smart Houses and the Dream of the Perfect Day, Duke University Press, United Kingdom.

Richard Harper (2003) Inside the Smart Home, Springer Publishers, New York.

Smart House: Your wish is Their command, Web.

Smart House: The so called Sci-Fi Life, Web.

Smart House Designs, Web.

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Smart Home Devices

Introduction.

Smart home devices have transformed home life. It has become essential to examine them from an ethical perspective, leading to the promotion of independent living with support from devices such as Amazon Echo reshaping the current life. In line with using the devices to maintain and improve functional capabilities, they have become tools whereby personal data can be used. Challenges within the smart home device use have been the ethical design and development. Understandable is the usage of devices that present various problems in promoting autonomy, privacy, and data security. Ethical concerns about smart home devices, such as the infringement of personal data, hacking, and irresponsible data sharing, require an in-depth evaluation. Hence, this paper examines that though these devices can create convenience for homeowners, knowing the risk challenges and many ethical concerns can help us address and mitigate these challenges in the future.

Background information about smart home devices and ethical issues

Smart home devices have taken a central position in contemporary society. With their adoption taking root more than a decade ago, the devices are geared toward improving home living. The devices rely on a network society for a better quality of life. Hassan et al. (2020) recognize that tools used in computer systems are integrated into smart home systems and play an essential part in improving daily life. Advancements within the field of smart home devices are not an isolated case. Firstly, the developments that occur are within the purview of the society that has been shaped by various trends (Stip & Rialle, 2005). Acknowledgment of the added value of the devices entails an intelligent setting shaped by the internet, Wi-Fi, smartphones, smart audio, visual devices, and interconnected computer systems (Stip & Rialle, 2005). On the other hand, smart devices such as smart speakers, home control, and thermal stat systems are deemed complex systems influencing daily life.

Reliance on smart home devices translates into an integrated home that can realize the interactive process between the user and technology. Obtaining information and establishing the parameter for an easy life translate into activities such as interconnected computers, television, and smartphones that can ease communication (Gerber et al., 2018). Further, smart home devices enhance comfort, safety, and interactivity by optimizing various activities. The facets of concern include ease at controlling the thermostat to one’s specification to orders from Amazon and control of information services at home (Hassan et al., 2020). Establishing a real-time platform whereby the devices improve the purchase and cross-interaction has a paradigm shift in operations.

Further, home appliance interactive control is also a feature of smart home devices that translates into ease of operations (Chan et al., 2009). Hosting services and automatic rational management of home appliances are evident through the internet. Further, home electricity management is also at ease which is positively influential.

Nonetheless, problems arise in the ethical setting, especially in data management. Critics such as Umbrello (2020) assert that privacy is a primary moral concern. The interactive process of devices highlights significant data collection. For example, Amazon Echo regularly collects personal data when sales are made, and questions arise on how the data is used by the organizations (Umbrello, 2020). Raised concerns on the interactive process of data from the smartphone to television in making outside interaction is equally a concern. The execution of normative ethics highlights that privacy shapes the tenets of evaluation. Emphasis on monitoring personal data comprises respect in its assessment (Wolf et al., 2019). Proper practices in data collection and access to the third party are equally essential to examine, which can lead to an assessment of the interests of multiple parties. Autonomy is an essential dimension in reviewing the drastic adoption of smart home devices. Awareness of the shared data highlights that the customers need help determining what is undertaken to safeguard their data. Examination of the ethical setting denotes establishing the standards for informed consent in the specificity of using smart home devices (Sánchez et al., 2017). Thus, the in-depth assessment of the parameters of smart home devices and ethics should align with examining the existent challenges. Acceptance that these devices can create convenience for homeowners and knowing the risk challenges and many ethical concerns can help us address and mitigate these challenges in the future.

Ethical issues in smart home devices

Acm code of ethics applies to smart home devices..

Computing devices and actions have led to considerable changes in the world. Thus, acting responsibly should reflect on the work’s and products’ broader impacts while promoting the public good. Sánchez et al. (2017) emphasize that the ACM code of ethics encourages the profession’s conscience and device used as the way forward. The code is construed towards designing, inspiring, and guiding the ethical code of conduct, especially for all computing professionals. Inclusive of current and aspiring professionals, the need to affirm principles of behavior can lead to positive outcomes (Sánchez et al., 2017).

An essential principle of ACM relatable to smart home devices is the need to contribute to societal well-being and acknowledge that people have vested interests in computing. People are critical to upholding the values and expectations of an effective decision-making platform (Nelson & Allen, 2018). The concerns of quality of life of all individuals should be within the use of computer products. The technology should also be adopted from an individual and collective setting to benefit society, workers, and the surrounding environment. People’s obligation is based on the promotion of fundamental human rights and conformity to the values of autonomy (Maalsen, 2020). Computing professionals aim to reduce negatable consequences of computing, such as safety, security, and privacy (Birchley et al., 2017). With multiple stakeholders’ interests, the users’ attention and priority should be geared toward autonomy, upholding human rights, and conformity to value-centric operations.

Therefore, it is fundamental to consider that computing tools should respect diversity while ensuring socially responsible initiatives. Meeting the citizen’s needs and being socially accessible is an influential parameters of technology use (Ehrenberg & Keinonen, 2021). Consequently, the basis for technological implementation is upholding the principles of a social environment that promotes human well-being.

On the other hand, respect should be geared toward the devices that can be the foundation for producing new ideas and promoting ease in the execution of multiple works (Erica, 2022). In technology use, it is crucial to respect copyrights and patents while ensuring that the protection of results prevails (Purkayastha, 2022). From custom and copyrights, the ACM code emphasizes that public and private computing goods should be within the paradigm of accessibility. Technology should be eared at helping society (Maalsen, 2020). From computer professionals to the computing process, it is essential to promote the principles of the ethical use and improvement of life. Equally central to the use of technology, the following values should be upheld.

Respect privacy

The ACM code is set on establishing responsible computing professionals who respect privacy. Arguably, technology is a tool that rapidly collects, monitors, and exchanges personal information. Privacy is vital with smart home devices showing extensive knowledge exchange (Sánchez et al., 2017). Therefore, the focus on conversing in the various definitions and forms of privacy can be the basis for understanding the rights and responsibilities. The collection and usage of personal information is a specific technology feature whose value can be examined extensively (Birchley et al., 2017). Technology should be used effectively to ascertain legitimate ends without violating the rights of individuals and groups. Consequently, precautions should be taken to prevent the re-identification of the anonymized data or unauthorized data collection.

Promoting the accuracy of data, ensuring understanding of the provenance of the data while promoting unauthorized access or accidental disclosure. Promoting transparent policies and steps that allow for comprehension of which data is being collected or used should be within the parameters of giving informed consent. Data collection should promote personal data’s value (Sánchez et al., 2017). For smart home devices, the amount of important personal information is usually collected in a system. Thus, it is vital for the retention and disposal periods of the information should be clearly stated, enforced, and communicated to the existent data subjects (Sánchez et al., 2017). Personal information from the devices should not be used for other purposes without one’s consent. Taking special care of privacy using devices should emerge when data collection.

Adequate privacy protection minimizes the level at which identifiable personal data is shared. Smart home devices, from television to smart speakers, phones, and computing systems at home, must maintain a balance against the need for data from users (Sánchez et al., 2017). Data usage should require particular attention to unauthorized access to in-home store data. Examining the viability of the security measures implemented to safeguard personal data should be the basis for decision-making.

Promotion of confidentiality in the use of data

Despite the ACM code focusing on computing professionals called upon to promote a confidential management process, ripple effects must prevail in the technology use. The developers of smart home devices should focus on privileged information, such as client data and financial information, to be protected confidentially (Grant, 2022). The code’s ethics requires assessing the nature of contents and the implications for disclosure. Thoughtful consideration of personal data should be consistent with managing sensitive information (Maalsen, 2020). Efforts should be geared at safeguarding high-quality and sensitive information effectively. Smart home devices, through their developers, should be geared toward promoting the dignity of customer data (Umbrello, 2020). Deviating from the ethically unacceptable ways of sharing data should shape access to smart home devices. Opportunities for inclusivity in assessing the devices should be aligned with confidentiality.

Ethical Analysis Framework

Beauchamp and childress’ principles model in analyzing smart home devices.

The principle of ethical autonomy plays an integral role in understanding the use of smart home devices. Accordingly, it is essential to respect the data of individuals the home devices collect. Application to the technology is within the purview of valuing people’s data and should not be viewed merely as good. Companies should deviate from the view of personal data as a way to earn money and share it with others (Maalsen, 2020). Focus on the ethical justification for the use of smart home devices should be based on acceptance of individual consent in the data use. The intersection between confidentiality protection and respect for autonomy should be the purview of decision-making (Purkayastha, 2022). Explicit personal consent in accessing data from smart home devices should be within the purview of operations. Reduction of data accessibility among the organizations should establish an enabling platform for the involvement of the devices in decision-making.

Non-maleficence

The principle is essential in examining smart home devices since it can be used to establish the parameter of not inflicting harm on others based on access to personal data (Maalsen, 2020). Addressing the principle denotes sensitization on the use of the technologies and how data accessibility can emerge. From hacking and sharing personal data on the dark web to governments using data obtained from unscrupulous sellers of intelligent home devices, it is crucial to examine the implications. Privacy-related harms to personal data should emerge from aspects such as stalking (Purkayastha, 2022). Therefore, the social and reputational harm of data sharing should form the basis of awareness for the customers or family members. Consideration of the non-maleficence principle should shift the burden in the data review (Wolf et al., 2019). Potentially harmful effects of data sharing should be examined as the basis for smart home device usage.

Real-life examples

From an ACM code of ethics perspective, the collective responsibilities of the organizations, professional computing stakeholders, and the public have assumed real-life examples. Arguably, notions of ethical data usage, privacy, and confidentiality have not been upheld (Sánchez et al., 2017). Companies have remained unwilling to strive to engage in professional communication on the implications of smart home devices.

For Nelson & Allen (2018), using routers at home requires tight security or encryption to ensure that the interconnected devices are not subject to data hacks. Numerous families have had to grapple with hacking incidents with detrimental outcomes. From posting their photos on public sites to stalking incidents, smart home devices are prone to unscrupulous or unwarranted access (Purkayastha, 2022). Arguably, the challenge for most families is developing simple to complex encryption processes that can ensure that even their children’s phones or personal computers may not be intruded upon.

Further, Sani (2022) emphasizes that a primary ethical dilemma of a smart home is the misuse of personal information. The Dark web has become a trove of illegal activities, such as selling credit card information to photos of children. In a technologically empowered home, it is unsurprising that credit card purchases are undertaken, which establish the foundation for hacks (Pirzada et al., 2022). Technologically empowered houses revolve around how businesses can use personal information. From browsing internet sites to making online purchases, information becomes open. Engaging equally with multiple online businesses translates into companies often sharing the info (Sánchez et al., 2017). Companies gather personal data to hyper-personalize online experiences (Purkayastha, 2022). Consequently, information sharing among businesses translates into individualized marketing. The accessibility to multiple sites the moment people browse often highlights the prospect of sharing information without consent.

Sánchez et al. (2017) assert that personal information is deemed the new gold traded across the online platform. Attempting to reach the customer base through accurate data is a facet of concern that raises concerns about privacy and confidentiality. Valuable data points are exploited for businesses to make money or advance their marketing agender (Ehrenberg & Keinonen, 2021). Amazon and Facebook, at times, have come under fire for the sale of personal data they gather from multiple platforms. The wide-reaching effects of personal data sales were evident, especially in the Cambridge Analytica scandal, whose information ranged from various platforms (Purkayastha, 2022). The recognition of privacy invasion and the implications of manipulating people from multiple platforms raises ethical concerns.

Lack of oversight and organizational acceptance of responsibility in sharing personal information is an ethical area. Fowler (2022) acknowledges that companies operate with impunity in sharing personal data. Comprising a blend of third-party to own smart home devices, gathering your information is expected. As a result, confusion and dilemma are apparent regarding data governance and responsibility. Using big data within the operational setting sheds light on the engagement of information-sharing and processing systems without consultation (Pirzada et al., 2022). Businesses must adopt a perspective in their data collection process and third-party selling. Despite many experts lobbying for corporate governance and local policies on data sharing, its widespread mismanagement is rife in big data companies.

Lessons learned

Personal data is easily accessible, and most importantly, with the devices interconnected through Wi-Fi, it is crucial to promote good security management. Creating a secure home should commence with the router, the foundation for efficient operations (Sani, 2022). What connects all devices is valuable and should denote an integrated operation dimension. Furthermore, setting unique passwords can lead to a daunting prospect of outside hacks (Chan et al., 2009). Additionally, emphasizing the highest degree of encryption is crucial and recommends the WPA2 as an effective platform that requires establishing an enabling platform to ensure third-party access does not emerge (Zhu et al., 2022).

Further, at-home mobile applications should use super-strong passwords. The devices are accessible for family members who need passwords for decision-making. Devices associated with mobile apps call for login credentials to establish a parameter for family engagement in their management (Ehrenberg & Keinonen, 2021). Creating a unique credential from each smart device and an account is the framework for safeguarding from infringement.

Future projections

Ai (artificial intelligence) to control homes.

AI will become a prominent feature in the management of homes. Its potential to establish systems that will control various facets of the house will lead to an ethical line requiring new evaluation (Nancy, 2022). Accordingly, establishing a dangerous territory in the management of homes will emanate from the ease at which people relinquish control to the systems. For example, the ethics of confidentiality will arise from the data management and tracking process that will be left to the AI. Encouraging intelligent systems to be a standard fixture in homes will raise concerns about their decision-making process. Since technology is flawed, it is crucial to examine informed consent and the parameters that should enable it to be independent in data management (Pirzada et al., 2022). The AI will be based on training and coding of data, which may be tainted by human bias. An AI that solely responds to historical, social inequalities may emerge, which may be detrimental to effective home systems management and privacy concerns. For example, a male-centric AI may assume the role of women in the homes and not engage in confidentiality or privacy management of data or monitoring of the home members.

Recommendations

Policies for smart home device providers.

Organizations should be held accountable for personal data. The way forward is to establish parameters for the data and coordinate with the members. The development of a firm moral sense, especially for customer data protection, is within the parameter of operations for the organization (Nancy, 2022). Data is valuable and undoubtedly continues to influence the contemporary customer targeting process. Organizations should liaise with customers to develop ethical data management.

Encourage a moral sense of data management.

Communication with the public should be an essential dimension of operations for organizations on the ethical value of preserving their data. Emphasis on instruction and an information-centric approach to the importance of data and ways to protect it should align with ethical expectations (Chung et al., 2016). Data protection measures and compliance procedures being open to the customers in their use of devices should prevail to ensure security and not leak or be misused.

Conclusions

Smart home devices are a trend that continues to shape contemporary society. Ease in daily life at home is a crucial transition to reshape the technical landscape. Accordingly, the devices can create convenience for homeowners, and knowing the risk challenges and many ethical concerns can help us address and mitigate these challenges in the future. Data management is an essential component that requires an in-depth analysis from privacy to confidentiality and informed consent; it is fundamental for people to examine the underlying issues. Smart home device owners should be aware of the ethical concerns associated with the use, and it is paramount to maintain awareness for positive outcomes is paramount.

Birchley, G., Huxtable, R., Murtagh, M., Ter Meulen, R., Flach, P., & Gooberman-Hill, R. (2017). Smart homes, private homes? An empirical study of technology researchers’ perceptions of ethical issues in developing smart-home health technologies.  BMC medical ethics ,  18 (1), 1-13.

Chan, M., Campo, E., Estève, D., & Fourniols, J. Y. (2009). Smart homes—current features and future perspectives.  Maturitas ,  64 (2), 90-97.

Chung, J., Demiris, G., & Thompson, H. J. (2016). Ethical considerations regarding the use of innovative home technologies for older adults: an integrative review. Annual review of nursing research ,  34 (1), 155-181.

Ehrenberg, N., & Keinonen, T. (2021, May). Technology is an enemy for me now: How innovative home technologies assert control beyond intent. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems  (pp. 1-11).

Erica, W. (2022). How to make your home more energy efficient – and get a tax break too.

Fowler, G. (2022). There’s a spy in your home, and its name is Alexa.

Gerber, N., Reinheimer, B., & Volkamer, M. (2018, August). Home sweet home? Investigating users’ awareness of innovative home privacy threats. In Proceedings of An Interactive Workshop on the Human Aspects of Smarthome Security and Privacy (WSSP)  (p. 2018).

Grant, C. (2022). Making Your Home Smart Can Make Your Life Easier.

Hassan, H., Jamaluddin, R. A., & Marafa, F. M. (2019). Internet of Thing (IoT) Smart Home Systems: Conceptual Ethical Framework for Malaysian Developers. In  Advances in Visual Informatics: 6th International Visual Informatics Conference, IVIC 2019, Bangi, Malaysia, November 19–21, 2019, Proceedings 6  (pp. 451-462). Springer International Publishing.

Leigh, K. (2022). Keep Your Smart Home Safe from Hackers; As Internet-connected devices in homes become more popular, so do the risks of unwanted intruders.

Maalsen, S. (2020). Revising the smart home as an assemblage. Housing Studies ,  35 (9), 1534-1549.

Nancy, K. (2022). When a Smart Home Is Too Smart for its Own Good, Smart-home systems can control everything from the lighting to the temperature to the music, but they don’t always make life easier for homeowners.

Nelson, B. W., & Allen, N. B. (2018). Extending the passive-sensing toolbox: using smart-home technology in psychological science.  Perspectives on psychological science ,  13 (6), 718-733.

Pirzada, P., Wilde, A., Doherty, G. H., & Harris-Birtill, D. (2022). Ethics and acceptance of smart homes for older adults.  Informatics for Health and Social Care ,  47 (1), 10-37.

Purkayastha, R. (2022). A Study on Ethical Issues and Related Solutions for Smart Home Technologies. In  Exploring Ethical Problems in Today’s Technological World  (pp. 272-287). IGI Global.

Sánchez, V. G., Taylor, I., & Bing-Jonsson, P. C. (2017). Ethics of innovative house welfare technology for older adults: A systematic literature review.  International journal of technology assessment in health care ,  33 (6), 691-699.9

Sani, C. (2022). Smart technology has benefits for seniors and caregivers, too.

Stip, E., & Rialle, V. (2005). Environmental, cognitive remediation in schizophrenia: Ethical implications of “smart home” technology. The Canadian Journal of Psychiatry ,  50 (5), 281-291.

Umbrello, S. (2020). Meaningful human control over smart home systems: a value-sensitive design approach. HUMANA. MENTE ,  13 (37), 40-65.

Wolf, M. J., Gotterbarn, D., & Kirkpatrick, M. S. (2019, February). ACM code of ethics: Looking back and forging ahead. In  Proceedings of the 50th ACM Technical Symposium on Computer Science Education  (pp. 801-802).

Zhu, J., Shi, K., Yang, C., Niu, Y., Zeng, Y., Zhang, N., … & Chu, C. H. (2022). Ethical issues of smart home‐based elderly care: A scoping review.  Journal of nursing management ,  30 (8), 3686-3699.

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Smart Home: Everything you need to know

Rapid technological progress, increasing digitization and ever larger data streams: The idea of a connected “smart” home is more topical and enticing than ever. But just what does “smart home” mean? Where do the roots of this technology lie? What are the benefits and risks? What will the smart home of the future look like? We look at the mega trend from various perspectives.

Everyday life made smart

Mr. Watson is late again. He has no time for breakfast. But at least he has the basic necessities: Bang on the minute, the coffee machine supplies his first hot drink, with the defined quantity of milk and froth. Mr. Watson quickly gets ready for a stressful day at the office. The motion sensor is activated and notifies the garage door, which now opens. In all the rush, he has forgotten to switch off the iron and light. No problem, he deals with that while underway via his smartphone. At the office, Mr. Watson activates the washing machine so that the washing is done just in time for when he knocks off work. Have the kids got back from school safely? A glance at the recordings made by the indoor camera in the entrance hall reassures dad.

Shortly before arriving home, Mr. Watson activates the robovac and the “after-work” scenario via smartphone. While the vacuum cleaner does its work, the living room is bathed in a cozy light. The heating ensures a pleasant, predefined temperature, while soft jazz music makes for a relaxed atmosphere. The shutters close later in the evening. That’s the signal for the outdoor camera in the garden to step into action and monitor the patio and garden.

Definition: What is smart home?

“Smart home” denotes the use of technical systems, automated processes and connected, remote-controlled devices in apartments and houses. The main objective of the functions is to improve the quality of life and convenience in the home. Other goals are greater security and more efficient use of energy thanks to connected, remote-controllable devices.

Home appliances , such as the washing machine, lights or the coffee maker, can be time-controlled. Devices like motion sensors, cameras, shutters or thermostats initiate user-programmed processes. The heart of the smart home is the central control unit, with which various smart components are connected and can be controlled from the PC, smartphone or tablet. Common wireless standards such as Wi-Fi, Bluetooth, ZigBee or Z-Wave are used for communication or controlling devices. The central control unit is also termed a hub or gateway.

Back to the future: History of smart home

It’s human nature to find ways that make everyday life easier and more pleasant. The area of “ home automation ” – in effect the predecessor of the smart home – was brought to life through technological progress, in particular through the Internet and computer. Science fiction literature in the 1950s portrayed the first visions of homes that are monitored and controlled fully automatically by machines. The 1999 Disney film “Smart House” was about household computers and the consequences when smart machines take on a life of their own. And Disney proved to be unintentionally visionary in the part of the movie where the house’s intelligent control unit develops the feeling of jealousy. In reality, it will likely be a few years before machines can “generate” emotions – fortunately.

Scientists have already been working for more than 30 years on connecting home appliances and automating their use. Yet it’s only been in the past 15 years that the issue of the smart home has aroused broad public interest. The main reasons: Current challenges as a result of trends like an aging society, greater environmental awareness and the related wish for a sustainable energy supply. Increasing digitization and new means of enhancing convenience in our own four walls were further factors that put the smart home at the center of public interest at the turn of the millennium.

The Fraunhofer inHaus Center, which was opened in Duisburg in 2001, is a lighthouse project in German-speaking countries. The project involves exploring and testing new system solutions and products from the smart home segment in a residential environment. “The House of the Present” in Munich showcased a connected home with centrally controlled electronic processes from 2005 to 2011. The first T-Com House from Deutsche Telekom in Berlin was opened to interested visitors in 2005. The focus of this model project was on connecting various home appliances and controlling them by means of different input devices.

Technological teamwork

For decades now, a wide range of different home appliances have helped make everyday life more pleasant, speed up processes and hence save time and work. So what additional benefits does the smart home deliver? Without the smart home, the impetus for a machine’s every action has to come from humans, who start processes manually and activate each device individually at the right time. The smart home relieves them of this work by enabling components to communicate with each other. Devices start, control and monitor specific processes in the home on their own, depending on the scenario and on the basis of how they are programmed. Interoperability is the magic word. If devices are interoperable, they can communicate with each other. Only then does the alarm system activate itself when the shutters are being closed. Only then does the heating switch itself off when the window is opened. If there is no interoperability between the elements, the home is simply not smart.

Apart from enhanced convenience, better energy efficiency and greater security are other key aspects. If a smart home thermostat communicates with the window contact via WiFi, it detects a window being opened and thus regulates the temperature. Such a thermostat switches the heating off as soon as it receives information that no one is at home any more from the sensors of other devices. Smart LED lights automatically emit different tones of color depending on the time of day and room. If the outdoor camera on the patio is activated as a result of movements on the property, it also puts the indoor camera on alert, since there might be the threat of a burglary. In homes with elderly inhabitants, a pressure-sensitive mat could notify relatives whether someone has got out of their bed as usual in the morning.

The way to a smart home of our own

How is a home transformed into a smart home? The required components can be installed and configured without any technical know-how. The following aspects should be taken into account in planning:

• An Internet connection and WiFi are required
• A smartphone or tablet are best suited for controlling and monitoring the devices
• A wireless network is modern, convenient and elegant, but transmission by cable is more secure
• Should the devices be programmable from the central control unit and interoperable, or is a standalone solution enough?
• Are all the devices connected using the same wireless standard (e.g. WiFi)?
• Starter sets are ideal for beginners, but usually only cover a single area: either energy efficiency, security or convenience
• The central control unit should be placed so that all the devices to be addressed are within its radius

My smart home is my castle – security and data protection

While many technologies deliver benefits, they also entail risks that users should be aware of and minimize. In the case of the smart home, connecting devices and communication by them via wireless connections such as WiFi harbor certain risks. First, personal data may be able to be misused (camera recordings, photos, etc.). Second, there is the risk of cyber criminals manipulating individual smart home components. As part of the latest Cyber Security Insights Report by the U.S. software company Symantec, more than 20,000 smart home users worldwide were surveyed, including 1,000 from Germany. The results show how people sometimes make it easy for online criminals to access data and devices:

The most common problems with securing the smart home

• 10 percent of German users don’t protect their home WiFi with a password
• Every one in ten doesn’t change the preset default password, 35 percent of users worldwide have at least one unprotected device, which makes the household prone to attack by online criminals
• 45 percent of those surveyed don’t know how to secure their WiFi or router
• 60 percent say they are not able to update the firmware

Yet those surveyed are aware of how important it is to protect personal data on the Internet, which also includes protecting the personal data of others. For instance, outside cameras should only film the owner’s property. There are models that allow the user to define the areas that are filmed. Although part of the neighboring property is captured on camera, these areas are grayed out or pixelated. In exceptional cases, public authorities are even allowed to use smart home user data for prosecuting crimes. However, given the current legal position, that’s only imaginable in the case of serious crimes, such as homicide. If the smart home is a rented apartment, access to the data of the window contacts and heating may be conceivable in order to examine whether the tenant has caused mold to grow through incorrect ventilation or there is a building defect.

10 tips for greater security

Just a few steps and rethinking old habits can increase security in the smart home significantly.

• Do not access personal information or social media accounts in unsecured wireless networks
• Install all available updates to security software as soon as possible
• Use the strong encryption method WPA2 for your WiFi
• Disable additional functions, such as a camera or microphone, on devices if you don’t absolutely need them
• Use strong passwords, ideally comprising ten upper-case and lower-case letters, symbols and digits
• Do not open attachments in e-mails from unknown senders without checking them
• Switch off connected devices when you don’t need them
• Change the default login data and passwords stored in the factory settings of the devices
• Switch from WiFi to cable connections where possible
• Use a central control unit with encrypted data transmission and local data storage

Smart future

The German smart home market will triple in volume to €4.3 billion by 2022, according to the study “The German Smart Home Market 2017-2022. Facts and Figures.” The annual growth rate in the coming five years will thus average 26.4 percent. By comparison: Traditional industries, such as mechanical engineering, have an average maximum growth rate of six percent per annum. The rapid pace of technological progress means many innovative smart home elements will be used in just a few years’ time. IKEA is working on a smart table that detects food with a camera and suggests recipes based on the ingredients. That reduces waste and enables existing food to be used better. In the future, smart mirrors will analyze our skin and recommend care products on that basis.

The popular vision in pop culture of the traditional robot as a home help will become reality in the coming years. The robot does the washing, serves food and drinks, and also provides the inhabitants with useful information on the side. We can follow the baking or cooking process live in the smart oven of the future thanks to a built-in camera. The toilet of the year 2030 will provide users with information on the state of their health and can even conduct pregnancy tests.

The next big evolutionary advance to cater for people’s needs for ecological sustainability and a better quality of life is the concept of the  smart city : Residents will commute to the office in autonomous  electric cars  or on connected  e-bikes . Parcels will be delivered by  drones . People will travel at high speed, without emitting pollutants, in the  hyperloop , a sort of gigantic vacuum tube system in which passengers or goods are conveyed in an airless tube by means of magnetic levitation technology. According to the tech visionary and Tesla CEO Elon Musk, the 570 km trip from San Francisco to Los Angeles will then take just 35 minutes. That means more time for old-fashioned things: a pleasant talk with the passenger, a recuperative midday nap on the way to the next meeting, or a good book made of real paper.

The most important questions and answers at a glance

The garage door opens as soon as you cross the doorstep, you can also switch off the lighting while you are out and about, and the outdoor camera helps ensure you are safe in your own four walls at night: “Smart home” denotes the use of technical systems, automated processes and connected, remote-controlled devices in apartments and houses. Its objective is to improve the quality of life and convenience in the home, as well as residents’ safety and security. Smart home applications also often ensure more efficient use of energy.

There are now a large number of different smart home applications that are all intended to make everyday life easier for us. If, for example, you are out and realize you have left the light on, you can switch it off very easily using your smartphone. Conversely, you can set the heating to the desired temperature or turn on the washing machine before you arrive home. Appliances like a robovac can also be controlled conveniently from your smartphone or tablet. Many components initiate user-programmed processes: If, for example, the shutters are closed, the outdoor camera and motion sensor are activated. Other home appliances, such as lights or the coffee maker, are instead time-controlled, in other words, are switched on and off automatically at defined times.

Smart home devices start, control and monitor specific processes in the home on their own, depending on the scenario and on the basis of how they are programmed. In particular, they relieve people of work if they communicate with each other: Only then does the heating switch itself off as soon as the windows are opened, for example. The heart of this system is a central control unit – also called a hub or gateway – via which the various components are connected with each other. Common wireless standards such as Wi-Fi, Bluetooth, ZigBee or Z-Wave are used for communication and controlling the technology.

What is probably one of the most crucial advantages of a smart home: Users are relieved of a lot of work since they no longer need to start individual devices and processes manually at the right time. At the same time, devices such as motion sensors or cameras ensure greater security by enabling your home to be monitored, even if you are on vacation, for instance. Thermostats or smart lighting also help save energy: The heating switches itself off as soon as a window is opened, for example. An advantage of all that is also that the smart home is relatively easy to set up – even without any technical know-how.

A question many people ask about the smart home is: Just how secure are the applications in my home? Indeed, there is the possibility that personal data may be misused, for example when a camera makes recordings. There is also the risk of hackers gaining access to smart home components and manipulating them. So how can the system’s security be increased? That can be done with just a few steps: Security software should be used and updated regularly, for example. Many users also do not use a password, or only use a weak one, for their network – a problem that can soon be remedied. In addition, individual device functions, such as microphones, can be deactivated if they are not needed.

One thing is very clear: the trend is toward the smart home. The German smart home market alone is expected to triple in volume to €4.3 billion by 2022. The rapid pace of technological progress means many new components will also enter the home in the future. The main focus of that is domestic robots. The next big step toward the future is the smart city, where not only households, but also cars, the infrastructure or drones will be connected with each other.

Last update: November 2017

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Smart Homes, Smarter Habits: Classical Conditioning in Home Automation

This essay is about the integration of classical conditioning in smart home automation from the perspective of a robotics programmer. It explores how stimuli, both positive and negative, are strategically employed to shape user behavior and habits within intelligent living spaces. The essay delves into examples such as artificial sunrise simulations and smart thermostats as applications of classical conditioning, emphasizing the subtle yet profound influence of technology on daily routines. The role of machine learning algorithms in adapting and refining responses over time is highlighted, showcasing the dynamic potential of smart systems. The ethical considerations surrounding the use of classical conditioning in home automation are discussed, emphasizing the need for a balanced approach that respects user autonomy and privacy. Ultimately, the essay underscores the responsibility of robotics programmers to create environments that not only cater to user needs but actively contribute to the development of smarter, healthier habits.

PapersOwl offers a variety of free essay examples on the topic of Classical Conditioning.

How it works

In the realm of robotics programming, the evolution of smart homes has sparked a revolution in how individuals interact with their living spaces. As a robotics programmer immersed in the intricacies of home automation, it is fascinating to observe the subtle yet profound impact of classical conditioning on shaping habits within these intelligent environments.

Smart homes, equipped with interconnected devices and sensors, have ushered in an era where technology seamlessly integrates into daily life. The art of classical conditioning, a psychological concept pioneered by Ivan Pavlov, has found an unexpected application in the world of home automation.

The parallel between Pavlov’s experiments with dogs and the programming of smart home systems lies in the association of stimuli with specific responses, creating a conditioned reflex.

Consider the scenario of waking up to an artificial sunrise simulated by smart lighting systems. The gradual illumination serves as a positive stimulus, linked to the waking routine. Over time, individuals form a subconscious association between the increasing light intensity and the act of waking up, essentially training their bodies to respond to this external cue. This is a prime example of classical conditioning at play in the realm of home automation.

In the programming landscape, the challenge lies not only in designing efficient algorithms but also in understanding human behavior to create a harmonious synergy between technology and habit formation. The concept of positive reinforcement, a key element in classical conditioning, is leveraged to reward desired behaviors within a smart home. For instance, a smart thermostat that learns and adjusts the temperature based on user preferences not only ensures comfort but also reinforces energy-efficient habits.

Conversely, negative stimuli can be strategically employed to discourage undesirable habits. Imagine a smart refrigerator that emits a subtle warning signal when a user reaches for an unhealthy snack. Over time, the association between the warning signal and the unhealthy choice becomes ingrained, potentially influencing the user to opt for healthier alternatives. This application of classical conditioning in smart home design extends beyond mere convenience to actively promoting well-being.

The integration of artificial intelligence further elevates the potential for classical conditioning in home automation. Machine learning algorithms, capable of analyzing user patterns, enable smart systems to adapt and refine their responses over time. This adaptability enhances the conditioning process, allowing for a dynamic and personalized experience within the smart home environment.

As a robotics programmer, the responsibility extends beyond writing code to understanding the delicate balance between automation and user agency. Striking this balance requires a nuanced approach, acknowledging the importance of user input while utilizing classical conditioning to subtly guide behaviors. It is about crafting an environment that not only responds to user needs but actively shapes habits for a more efficient and fulfilling lifestyle.

However, the ethical implications of employing classical conditioning in home automation cannot be overlooked. The fine line between convenience and manipulation raises concerns about user autonomy and privacy. Striking the right balance between influencing behavior for the better and respecting individual choices is a paramount consideration in the development of smart home systems.

In conclusion, the marriage of classical conditioning principles with the realm of home automation presents a captivating frontier for robotics programmers. The subtle influence of stimuli on user behavior within smart homes underscores the potential for a positive impact on daily habits. As technology continues to advance, the role of the robotics programmer extends beyond the technical intricacies to shaping a future where smart homes not only respond to our needs but actively contribute to the development of smarter, healthier habits.

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• Research Article
• Open access
• Published: 06 May 2021

The social issues of smart home: a review of four European cities’ experiences

• Saeid Pira   ORCID: orcid.org/0000-0002-8176-4226 1  

European Journal of Futures Research volume  9 , Article number:  3 ( 2021 ) Cite this article

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12 Citations

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The urban industrialization trend and the increasing urban population have posed global and local concerns related to urban management. Today, scientists introduce the “smart city” concept, among many others. The primary concept purpose is to empower cities to enhance the quality of life of their residents. To achieve this, one of the smart city components named “smart living” has a direct connection to citizens’ quality of life. This research aims to analyze the smart home as one of the sub-components of smart living. Consequently, based on the “smart home” residents’ viewpoint, the main question is which social barriers are more critical?

To achieve this essay’s objectives, the researcher conducts three phases: data collection, analysis based on the constructed conceptual model, and results. The researcher selected four leading smart cities in Europe, including Copenhagen, Berlin, London, and Barcelona, as case studies. The study collected primary data by cluster-random sampling by utilizing a questionnaire survey with 320 participants. In conclusion, according to the inhabitants, the research results list the most significant social challenges in smart homes. Eventually, suggestions offer for reducing the side effect of living in a smart home.

Introduction

The world has witnessed an increasing accumulation of its people in urban areas since 1990. This trend is not new and represents a substantial increase in urban residents’ number, from an approximate average of 57 million between 1990 and 2000 to 77 million between 2010 and 2015 [ 1 ]. It poses significant challenges for the environment and social sustainability. Also, the contemporary structure of cities is a source of environmental and social dilemmas. Cities consumed approximately 70% of the world’s resources and are also significant users of energy resources. Hence, they became the main contributors to greenhouse gas (GHG) emissions. The growth of the urban population and the intensity of economic and social activities are triggering this crisis. It is also a consequence of the built environment inefficiency. Current research in urban and academic circles focuses on sustainability in urban planning. Besides, they try to address the main urbanization challenges and the unsustainability of existing structures [ 2 ]. The smart cities concept emerged as an appropriate solution to this unprecedented urbanization and the need for sustainability. Therefore, this idea attracted plenty of academic interests in this field [ 3 ]. The International Telecommunication Union Focus Group on Smart Sustainable Cities (ITU-T FG-SSC) introduced a definition, which reads as follows: “A Smart Sustainable City is an innovative city that uses Information and Communication Technologies (ICTs) and other means to improve quality of life, the efficiency of urban operation and services, and competitiveness while ensuring that it meets the needs of present and future generations concerning economic, social, environmental as well as cultural aspects” [ 4 ]. One of the components of the smart city concept is “smart living.” I will explain these criteria in the following sections. The smart home is one of the essential sub-components of this component, which splits into two sections: (1) state-of-the-art technologies and applications and (2) the behavior of the residents who live in these homes. It is crucial to note that city dwellers have contradictory comments about smart home applications. According to the research findings, the way to overcome the social barrier and to communicate with state-of-the-art technologies is the key worry of smart home residents. This research aims to find the most concerning social issues for smart homeowners. For this purpose, four European cities (Barcelona, Copenhagen, Berlin, and London) select as case studies. Finally, this study suggests several recommendations to reduce identified social issues.

Literature review

The idea of smart cities was rooted in the 1970s when a digital configuration based on technology and non-material structures embedded in the urban physical spaces. Afterward, the new aspects of everyday life have been concentrating on more complex innovations. Broadband networks and collective intelligence determining the city development supported these new technologies [ 5 , 6 ]. There are different views regarding the origin of the concept of “smart city” in the literature. According to Caragliu et al. (2009), “The city could be smart when investments in human and social resources combined with traditional and modern ICT infrastructures boost sustainable economic growth and high quality of life, with wise natural resource management through participatory governance [ 7 ].”

Globalization trends and emerging new technologies are increasingly influencing urban and regional environments. ICTs are also heavily involved in the management and governance of cities. Authorities and planners use these innovations as tools and services to promote the quality of life, promote a sustainable development, and create a more dynamic and innovative urban landscape [ 7 ]. Over time, scholars, institutions, and large corporations provide expressions such as digital, smart, ubiquitous, wired, hybrid, information, creative, learning, humane, knowledge, and smart cities. The significant purpose is to describe the renewed configurations adopted within the local context [ 8 ].

Smart city definitions

There are different views regarding the origin of the concept of “smart city” in the literature. According to Garby (2014), the roots of the concept date back to the 1960s, and in urban development plans, it figures in proposals for networked cities since the 1980s. Also, Dameri and Cocchia (2013) claimed that specialists introduced this concept in 1994 [ 9 ]. The roots of this term, according to Neirotti et al. (2014), can be traced back to the late 1990s smart growth trend [ 10 ]. That said, it involves growing urban efficiency-related to energy, transport, land use, communication, economic development, service delivery, and so forth. A smart city is an effective strategy focusing on the ICT-based leadership of metropolitan areas [ 11 ]. The technological dimension is currently significant in the smart city definition: innovative approaches focused on the Internet network are the basis for a smart city. Besides, the development of a high-quality infrastructure for urban ICT is an integral part of a smart city. Coherent research produced by technology suppliers highlights the importance of this component. Furthermore, it claims that private companies engaged in telecommunications, transport, software, informatics, and electricity are pushing forward the smart city concept [ 12 ].

Two of the most relevant concepts will sum up the various variables that define the conceptualization of smart cities:

We believe that a city is smart when investments in human and social capital and conventional (transport) and modern (ICT) connectivity networks boost sustainable economic growth and high quality of life through participatory governance, wise management of natural resources.

The more recent interest in smart cities can be due to concern for sustainability and the emergence of new Web technologies, such as mobile devices, the semantic internet, cloud computing, and the Internet of Things (IoT), which facilitate the real-world user interfaces [ 13 ].

The central point posed by numerous scientists in the smart city concept is the role of ICT in today’s cities and the need to enhance emerging technologies. They claim that improving the quality of life of citizens is inevitable without access to these technologies.

Smart city features

The concept “smart city” is a bit fuzzy since it encompasses a wide range of dimensions and characteristics. According to Nam and Pardo, there are many definitions and considerations relevant to smart cities that contribute to technological, human, and institutional aspects (2011) [ 14 ].

Smart cities include the human capital variable as the main element of increasing interest in knowledge-based financial growth and innovation. In addition to being a “new engine” for sustainable development, the involvement of a trained and professional population and workforce is an essential component of this concept. The smart city’s employees should be well-trained and creative, with access to other knowledge-sharing opportunities [ 15 , 16 , 17 ]. The combination of technical and human dimensions allows for the development of a technologically advanced and imaginative network. It is a common strategy to achieve urban development and de-industrialized finance. The utilization of development and social capital through “smart urban communities,” composed of firms, education, government, and individuals, depicts the smart city’s organization. These communities benefited from ICT and human capital to engage all participants to innovate and beneficially alter the urban environment [ 14 , 18 , 19 ].

Smart city characteristics

According to studies, a smart city would have five key components: contemporary technologies, buildings, utilities, transportation, and road infrastructure. In terms of technology, a smart city is a long-term collaboration between government, government institutes, and private companies to develop and implement computerized platforms. This cooperation is concerning with strengthening contemporary technologies, including mobile cloud computing, digital documents, networks, and emerging decision-making methods [ 20 , 21 ].

Smart city notions are as broad as the number of smart cities. Besides the three dimensions explained in Table 1 , the following six characteristics should include “smart economy,” “smart people,” “smart governance,” “smart mobility,” “smart environment,” and “smart living” Those three dimensions influence the outcomes of the six characteristics. Table 2 shows the theories and the characteristics of each of these six characteristics [ 14 ]:

Smart living is one of the characteristics of the smart city, according to the table, and the crucial purpose of this component is to boost citizens’ quality of life. There are also other aspects of smart living, such as education, safety, and social cohesion.

As stated, the primary goal of smart cities—especially smart living component—is to improve the quality of life of citizens. In this regard, one of the practical recommendations for achieving smart living is the idea of smart homes. One of the realistic alternatives to implementing smart living is the “smart home” idea. Its principal goal is to combine system, service, and management to provide people with an efficient, comfortable, safe, accessible, and environmentally friendly living environment.

Smart home definitions

Scientists used multiple notions to describe and conceptualize smart homes (Table 3 ). Among various approaches, the definition by Aldrich (2003) and Lutolf (1992) dealt inclusively with the nature of smart homes. A smart home, according to Aldrich (2003), is “a house designed with computer and information technologies that anticipates and responds to the needs of the inhabitants, functioning to facilitate their comfort, ease, security, and entertainment through the management of home technologies and connecting to the world beyond.” This definition encompasses the phenomenon’s technical component, as well as the services and functionality it provides. It is worth noting that smart homes would respond to a wide range of attitudes [ 23 ]. Besides, Lutolf (1992) described a smart home as “integrating various facilities through the use of a communication scheme in a home. It ensures an economical, safe, and comfortable home operation and involves a high level of smart functionality and flexibility.” [ 24 ] Although the two definitions share similar viewpoints, they differ in terms of the technology’s capabilities and the types of customers it seeks to serve. Many academics associate smart homes with technological features in general [ 25 ].

As mentioned above, there are differing views on the idea of the smart home. The author’s point of view in this article is closer to the theories of Aldrich and Lutolf. According to these two scientists, the smart home theory is based on the use of ICT and houses equipped with computer and information technologies. Also, the author considers two factors of functionality and flexibility in this article.

_ Smart home types of services:

Researchers used practical analyses to evaluate these home technologies, which would provide a variety of services to residents. The below are some of the smart home’s core features:

The smart home has the potential to improve the consumer and power grid relationship. It assists in data collection on power use, energy costs, and an energy use plan establishment. Smart homes also monitor the efficient use of resources and promote family awareness of energy conservation and environmental sustainability.

A smart home can enhance the lifestyle by promoting home security, safety, accessibility, and interactivity.

A smart home could support remote payment.

Smart homes can use a computer, a mobile phone, and a remote network to monitor and connect with the house.

Smart homes consider the real-time meter reading and security service of the water meter, electric energy meter, and gas meter to provide more efficient and high-quality services.

Supporting the “triple networks” industry and providing the ideal smart service [ 26 ].

In recent years, numerous scientists have conducted studies on smart home services, functions, and devices, as seen in Table 4 . The majority of the reviewed papers (41 articles) discussed ensuring a comfortable life. After that, most studies related to the monitoring service (31 references). In contrast, fewer articles focus on health therapy and the supportive functions of smart home technology. Only two papers discuss the consultancy service that smart sensors provide [ 22 ].

“Smart city” and “smart home” connection

The connection between smart cities and smart homes requires multiple applications across numerous fields. There is a term that defines this connection unequivocally, and that is “big data” ( https://www.smartcity.press/how-smart-homes-can-connect-smart-cities/ ). Data generates from multiple sources resulting in the formation of what is currently known as big data. Data sources are ubiquitous around us as smartphones, computers, environmental sensors, cameras, GPS (Geographical Positioning Systems), and even city dwellers. Multiple applications like social media, digital pictures and videos, commercial transactions, advertising applications, games, and many more exacerbated data generation in the past few years [ 27 , 28 ].

The significance of big data is undeniable. In other words, big data has a critical effect on several aspects of smart cities and, eventually, on citizens’ lives [ 29 ]. Smart city applications store information, and big data networks utilize this information. Also, big data systems gather information and process it to enhance the multiple services of smart cities. Big data will also help authorities to plan the development of smart city services. There are numerous instances of big data applications that serve the smart cities:

1 Smart education: Through education facilities, ICT offers solutions for improving the quality, efficiency, and profitability of educational systems. These facilities are adaptable in their use of information, better monitoring, and evaluation and expanded learning opportunities for citizens and stakeholders [ 30 ].

2 Smart traffic lights: one of the main features of smart cities is effective traffic flow control, which will improve transportation systems and improve the traffic patterns of citizens and the city as a whole [ 31 ].

3 Smart Grid: Smart grid is a vital component of smart cities. It is a reconstructed network that gathers and operates on existing data, such as information about suppliers and customers’ behaviors, utilizing information, and communication technology in an integrated manner to incorporate values [ 32 ].

Smart cities and big data are two modern approaches. Hence, numerous scientists have begun integrating them to develop smart city technologies that will enhance sustainability, improved resilience, efficient government, quality of life, and resource management. Big data applications have the potential to serve many sectors in a smart city. It provides clients improved experiences and lets businesses improve their performance (e.g., higher profits or market share). Also, improve healthcare by improving preventive care services, diagnosis and treatment tools, healthcare records management, and patient care. Big data will significantly help transportation networks to optimize roads, accommodate varying demands, and be more environmentally friendly. Deploying big data applications requires the support of adequate infrastructure for information and communication technology (ICT). Smart cities benefit from ICT since it provides appropriate solutions that would not be available without it [ 33 ].

On the other hand, some of the issues that smart cities face while using big data include:

Data sources and characteristics

Data and information sharing

Data quality

Security and privacy

Smart city population [ 34 ]

Some features of the smart city concept related to big data are mention in this section. Consequently, big data is an essential subject in smart cities to support the residents’ security, safety, education, and application. These features are part of the smart living sub-components. One of the six characteristics of the smart city concept—which includes many features including safety, housing, and education—is smart living. The findings of the study revealed that big data and smart living are inextricably connected.

This research aims to assess the social barriers in smart homes, one of the sub-components of smart living. As reviewed, big data interwove to smart homes and smart cities. Consequently, we can achieve the smart city’s established objective by developing big data services.

Pros and cons of smart homes

Smart homes are one of the EU’s ten main fields in the strategic energy technology plan: “Create technologies and services for smart homes that provide smart solutions to energy consumers.” The commission aims to promote creative ideas and manage consumers and authorities to optimize their energy consumption (and production). It also enables cities to manage energy usage, relying on smart grid services, through a more interactive/smart system [ 35 ].

Smart home technologies (SHTs) incorporate sensors, monitors, interfaces, appliances, and mobile devices to enable household environment automation and remote control. Sensors and monitoring systems control environmental variables like temperature, light, movement, and moisture. Computer applications (smartphones, tablets, laptops, PCs) or specialized hardware interfaces (e.g., wall-mounted controls) support the control systems. The main goals, vital advantages, and the most relevant problems of smart homes are listed in Table 5 [ 36 ]:

Smart homes’ social barriers

Despite the advantages and disadvantages of new technologies in current urban areas, the use of smart homes is inevitable. We concentrate on the most significant smart home issues in this article. Generally speaking, these problems can divide into two parts: (1) Technological and instrumental concerns and (2) obstacles raised by users of such tools. This paper aims to analyze the challenges of smart homes (especially societal barriers). Table 6 shows the research findings of several articles on this subject.

Multiple social barriers have been found in previous research, according to the table. In this research, a group of urban planners and social scientists looked at these obstacles and divided them into four categories. These components are as follows:

Privacy and security

Reliability

Satisfaction

Trust on device controlling.

Conceptual model

The previous reviews and the author’s findings support the conceptual model in this study. The following graph depicts the study’s conceptual model and, essentially, the researcher’s perspective. The “smart city” concept, according to scientists like Carlo Carpa, consists of six components, each of which is composed of several theories and features (Table 2 ). Smart living, among these different indicators, aims to improve the quality of life idea. And its features include education, culture and health, facilities, safety, housing, social cohesion, and tourist attractions. This research aims to analyze smart living and especially the social barriers of smart homes. In this regard, previous studies identified several factors as the most significant social issues of residents. These criteria include privacy, security, reliability, satisfaction, and device control. Finally, the author of this article selects these factors as criteria for assessing residents’ satisfaction with living in smart homes. Figure 1 describes the conceptual model in detail.

Conceptual model. Source “by the author”

This paper needs to examine its set indicators in a case study to achieve the research objectives. For this purpose, four European cities (Copenhagen, Berlin, Barcelona, and London) are selected as the case studies. It is worth noting that this paper aims to recognize the social barriers based on resident’s experience in smart homes. The author defines four criteria to measure the social issues, then conducts interviews with residents to assess the effect of these criteria. Finally, based on the residents’ comments, the significant social barriers of smart homes are identified.

In 2018, the Eden Strategy Institute ranked smart cities in the globe base on multiple criteria. This study rate 50 smart cities across the globe. The Berlin city is rated 29th in the report, Copenhagen 24th, Barcelona 9th, and London 1st. In this article, the researcher chose 4 European cities. Each of these countries made significant strides as a leader in the smart city concept. While residents are willing to embrace state-of-the-art technologies, several issues have created obstacles among these residents. The questionnaires will help evaluate the components after choosing the case studies to answers the research questions.

To accurately analyze these four components, a group of experts from various fields identified several sub-components. The group includes seven experts in the fields of urban planning, regional planning, urban design, and architecture. Also, these experts have extensive expertise in the area of urban planning and management. Table 7 is a list of the expert group criteria.

Table 8 presents the indicators and sub-indicators analyzed in this study. The author addresses these variables in the questionnaire questions.

The questions in the questionnaire comprise sub-components determined by the expert group. In this way, we will identify the social issues that trigger dissatisfaction among smart home residents. The questionnaire is composed of two parts. Part one contains socio-demographic questions (age of respondent, the gender of the respondent, profession, household income) and a specific question regarding smart homeowners’ academic studies. The screening question seeks to find the best people’s responses to the assessment. The screening query was “What are digital home technologies?” Options of response range from “no idea,” “primeval information,” and “good Information.” Respondents who replied “no idea” removed in this part. We will need residents who are knowledgeable regarding smart appliances to find the research goal. To this end, the research did not analyze the views of those who believed they lacked expertise in this field. The next section of the survey begins with an open-ended question asking respondents to give a few phrases about “What first comes to mind when you think of smart home technologies?” This question allows us to get a deeper understanding of how respondents think about smart home technology. Finally, the researcher assessed the interviewees’ opinions, and the responses were graded in the range 1 to 10 to evaluate each sub-indicator.

The research gathers primary data from 320 smart homeowners through random-cluster sampling via the adoption of a questionnaire study. So the researcher filled out 80 questionnaires at each sample city. The selection of interviewees is a crucial part of this research. Smart homeowners living in houses fitted with the latest technology are the interviewees in this study. Accordingly, the research group distributed the questionnaires to residents of the smart home in the four cities surveyed. Researchers select 80 residents of smart homes in each of those four cities. The investigator identified these families by associates in each of these cities. He contacted them and explained the goal of this study, and sent the questionnaire to them. To receive diverse viewpoints, the researcher chose interviewers with different characteristics. The characteristics of the people who filled out the questionnaires illustrate in Table 9 . It should mention that the author emailed the questionnaires to identified people due to the dispersion of the case studies. Then, the interviewees sent the completed questionnaires to the researcher.

The author picked the respondents from different age groups and genders as well as various social groups. The following tables provide some information about all 320 interviewees. Also, Fig. 2 presents the gender distribution:

The distribution of respondents by gender. Source “by the author”

Table 10 shows the number and percentage of respondents by age group.

The details of the interviewees’ academic rate are set out in Table 11

The author of this study explores four metrics as criteria for measuring social issues within smart home residents. The following graph depicts residents’ concerns regarding smart homes in four cities. The least concerning factor of these four indicators, according to the interviewees, was privacy and security. This measure has the highest percentage, meaning that residents are the most satisfied with it. In contrast, they state that their significant concern is trust in controlling devices (Fig. 3 ).

The contribution of each social barriers in smart home. Source “by the author”

The bar figure below illustrates each city’s score depending on the chosen measures. The city with the highest score is Copenhagen, while London has the lowest score. On the other hand, the two cities of Berlin and Barcelona also rank second and third respectively. It is worth noting that the lower a city’s ratings, the less effective it is in terms of social concerns, and residents face more social issues.

Copenhagen placed in the fifth position based on the world’s happiest cities in the World Happiness Report (WHR) 2020. The satisfaction of citizens living in this country is at a very high level. The survey included criteria such as life expectancy, security, and satisfaction with living in cities, which indicates a high level of quality of life in this city. On the other hand, in this research, the author aimed to make sure that the resident’s satisfaction in different cities does not affect how they react to the questionnaire. And only their concerns about the social factors mentioned in the questionnaire should analyze. Instead of dwelling on whether or not they are happy with living in their cities, the questionnaire focuses on the most significant social obstacles they face in their smart homes (Fig. 4 ).

The scores of each city based on the criteria. Source “by the author”

The bar figure below illustrates the scores for each indicator in 4 cities. Each indicator’s value was determined using a 1 to 10 ratio. It means that the higher a criterion’s indicator score is, the less worried residents are about it. Overall, Copenhagen outperformed the other three cities in each of these measures. Another point to remember is the low level of confidence in control devices. The privacy and security parameter, on the other hand, was the least troubling indicator. The following sections go into the details of each city’s situation:

Copenhagen: The “privacy and security” component in this city has the lowest level of concern among the smart home’s residents. Also, they state that “trust in controlling devices” is the significant troublesome among the indicators analyzed in this research. Also, the other two components are in a better position.

Berlin: “Privacy and security” in this city have a lower score than in Copenhagen. However, this component has more favorable conditions than the other two cities. In this city, “trust in controlling devices” has the lowest level of satisfaction among respondents.

Barcelona: The equality of the scores of the two components—“privacy and security” and “reliability”—is a significant point in this city. As a result, these two components have the highest level of satisfaction. While “trust in controlling devices” has the lowest level of residents’ satisfaction.

London: The point that clear in this city is that almost all the components scored fewer points than the other three cities. Also, the residents’ satisfaction trend in this research is similar to the other three examples. As a result, the highest level of satisfaction is associated with “privacy and security,” while the lowest level of satisfaction is related to “trust in controlling devices” (Fig. 5 ).

Criteria scores of social problems by city. Source “by the author”

The author appropriates several sub-components in this research for an accurate analysis of the components. These sub-components are the result of discussion and consultation obtained from the expert group. The conclusions derived from the sub-component analysis illustrates in the following diagram (Fig. 6 ).

Sub-criteria scores of social problems by city. Source “by the author”

Table 12 represents the scores of the sub-component by city. Furthermore, a separate column shows the average score of each component. Based on the average scores, the “privacy and security” component has the highest score (8.4), therefore has the highest level of satisfaction among smart home residents. In contrast, “trust in controlling devices” has the lowest score (6.4), reflecting resident frustration with smart homes. It is worth noting that among all the sub-components, “smart surveillance systems” with a score of 9.5 have the highest level of satisfaction in Copenhagen. In contrast, several sub-criteria in the two “satisfaction” and “trust on controlling devices” criteria scored the lowest.

According to interviews findings in Copenhagen, the reason for their high level of satisfaction is the government’s monitoring of smart surveillance systems. In other words, government agencies’ oversight of the non-governmental service providers has increased public satisfaction. On the other hand, some residents in the other three cities are dissatisfied with the smart services provided by private and public companies. They suppose that the operation of several smart devices at the same time will cause issues due to the lack of monitoring of these systems.

According to smart home definitions, scientists state that such houses seek to utilize up-to-date technologies such as the internet to create more beneficial homes. It is important to consider that smart homes aim to improve the inhabitants’ quality of life besides their satisfaction. The advantages of designing smart homes are increasing economic growth, security, time savings, and pollution mitigation. On the other hand, the utilization of such services raises multiple challenges and concerns. One of the obstacles is the residents’ satisfaction with the use of these services. For instance, dependency on the Internet, interference in people’s privacy, and high expense of accessing such services. The most significant purpose of this article is to analyze the social issues of smart home residents. The primary goal is to identify such barriers. Also, what is the most significant social obstacles for residents? The most concerning social barriers describe below according to the case studies findings.

Trust on controlling devices.

Service satisfaction.

The reliability of the services.

Privacy and security.

According to interviews, the most significant issue is related to devise management. Respondents are concerned about how several devices operate simultaneously. To prevent such disorders, control officials must supervise the accurate performance of each of these smart devices. Also, experts should perform experiments to examine how multiple devices interact at the same time to identify potential troubles. This surveillance would improve consumer’s trust and lead to the increased utilization of these technologies in non-smart homes. Besides, companies should have periodic checkups to inspect the equipment to resolve any new issues. Eventually, through these approaches, citizens’ services improved to offer people satisfaction with smart home services. The last section provides the most significant recommendations to mitigate the challenges and facilitate the safe and effective use of smart home applications.

User recommendations

Home energy services are primarily responsible for appliance power consumption data, performing energy efficiency assessments of household appliances, and making recommendations about household power consumption. The technology-based systems present recommendations for users to reduce energy consumption. A device provides suggestions for mobile users when an intruder is detected. To decrease power consumption and the cost of household appliances efficiently, we recommend that users commit to the set runtime.

Health recommendations

Health institutions are primarily responsible for assisting and ensuring high-quality medical applications in smart homes and healthcare in general. Health institutions support the elderly (at home) by providing correct instructions, such as appropriate exercises through TV tutorials. Recommendations are given to patients in smart homes, including medical guidelines, patient diagnoses, and assistance for the elderly and people with disabilities. Such technologies can also determine and predict unexpected incidents such as fall injuries in smart homes.

Safety recommendations

Another advantage of using technology-based devices in smart homes is increased safety. People of all ages require specific healthcare, especially the elderly, and children often need guidance and help from those around them. Using a monitoring system provides appropriate supervision for homeowners if they are not at home. Also, ensuring that strangers do not enter smart homes are other benefits of using these homes. As a result, homes equipped with these applications will bring higher satisfaction to homeowners. Furthermore, smart devices provide instructions on how fire systems and electrical appliances are utilized and managed. A recommendation system to manage IoT–network relationships between IoT devices, networks, and operation techniques helps implement appropriate schemes, diagnose errors in smart homes.

Limitations

The most crucial section in this research was designing the questionnaire and assessing questionnaire data. Several experts evaluated the questionnaire indicators, then sub-criteria were identified for a more detailed study. It should note that this process was very time-consuming. Another obstacle in this research was finding informed people about smart homes to fill out the questionnaire. To sum up, smart home technologies face serious challenges. Further study and practical solutions to address the problems that lay ahead would pave the way for such technologies extension.

Availability of data and materials

All sources of data and materials analyzed in the course of this paper a listed in the reference section.

United Nations Human Settlements Programme (2011) Cities and climate change: global report on human settlements, 2011. Routledge

Bibri SE, Krogstie J (2017) Smart sustainable cities of the future: an extensive interdisciplinary literature review. Sustain Cities Soc 31 :183–212

Article   Google Scholar  

Nam T, Pardo TA (2011) Conceptualizing smart cities with dimensions of technology, people, and institutions. In: Proceedings of the 12th annual international digital government research conference: digital government innovation in challenging times, pp 282–291 ACM

Chapter   Google Scholar  

Ibrahim M, El-Zaart A, Adams C (2018) Smart sustainable cities roadmap: readiness for transformation towards urban sustainability. Sustain Cities Soc 37 :530–540

Ishida T, Isbister, K. (Eds.). (2000) Digital cities: technologies, experiences, and future perspectives. Springer Science & Business Media

Bifulco F, Tregua M, Amitrano CC, D’Auria A (2016) ICT and sustainability in smart cities management. Int J Public Sector Manage 29(2):132–147

Anthopoulos LG, Tougountzoglou TE (2012) A viability model for digital cities: economic and acceptability factors. In: Web 2.0 Technologies and Democratic Governance. Springer, New York, pp 79–96

Hollands RG (2008) Will the real smart city please stand up? Intelligent, progressive, or entrepreneurial? City 12(3):303–320

Dameri RP, Cocchia A (2013) Smart city and digital city: twenty years of terminology evolution. In: X Conference of the Italian Chapter of AIS, ITAIS, pp 1–8

Google Scholar  

Neirotti P, De Marco A, Cagliano AC, Mangano G, Scorrano F (2014) Current trends in smart city initiatives: some stylized facts. Cities 38:25–36

Jucevičius R, Patašienė I, Patašius M (2014) Digital dimension of a smart city: a critical analysis. Procedia-Soc Behav Sci 156:146–150

Caragliu A, Del Bo C, Nijkamp P (2011) Smart cities in Europe. J Urban Technol 18(2):65–82

Schaffers H, Komninos N, Pallot M, Trousse B, Nilsson M, Oliveira A (2011) Smart cities and the future internet: towards cooperation frameworks for open innovation. In: The future internet assembly. Springer, Berlin, pp 431–446

Capra CF (2016) The smart city and its citizens: governance and citizen participation in Amsterdam Smart City. Int J E-Plan Res (IJEPR) 5(1):20–38

Shapiro JM (2006) Smart cities: quality of life, productivity, and the growth effects of human capital. Rev Econ Stat 88(2):324–335

Florida R (2003) Cities and the creative class. City Community 2(1):3–19

Campbell T (2012) Beyond smart city: how cities network, learn and innovate. Earthscan, New York

Moretti, E. (2013). The new geography of work. Mondadori Editions.

Lindskog H (2004) Smart communities initiatives. In: Proceedings of the 3rd ISOneWorld Conference, vol 16, pp 14–16

High, P. (2015). The top five smart cities in the world. Forbes. com.

AlDairi A (2017) Cybersecurity attacks on smart cities and associated mobile technologies. Procedia Comp Sci 109:1086–1091

Marikyan D, Papagiannidis S, Alamanos E (2019) A systematic review of the smart home literature: a user perspective. Technol Forecasting Soc Change 138:139–154

Aldrich FK (2003) Smart homes: past, present, and future. In: Inside the smart home. Springer, London, pp 17–39

Lutolf R (1992) Smart home concept and the integration of energy meters into a home-based system. In: Seventh International Conference on Metering Apparatus and Tariffs for Electricity Supply, pp 277–278 IET

Balta-Ozkan N, Davidson R, Bicket M, Whitmarsh L (2013) Social barriers to the adoption of smart homes. Energy Policy 63:363–374

Li M, Gu W, Chen W, He Y, Wu Y, Zhang Y (2018) Smart home: architecture, technologies, and systems. Procedia Comp Sci 131:393–400

Khan Z, Anjum A, Kiani SL (2013) Cloud based big data analytics for smart future cities. In: 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing, pp 381–386 IEEE

Michalik P, Štofa J, Zolotova I (2014) Concept definition for Big Data architecture in the education system. In: 2014 IEEE 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI), pp 331–334 IEEE

Pantelis K, Aija L (2013) Understanding the value of (big) data. In: 2013 IEEE International Conference on Big Data, pp 38–42 IEEE

Tantatsanawong P, Kawtrakul A, Lertwipatrakul W (2011) Enabling future education with smart services. In: 2011 Annual SRII Global Conference, pp 550–556 IEEE

Galán-García JL, Aguilera-Venegas G, Rodríguez-Cielos P (2014) An accelerated-time simulation for traffic flow in a smart city. J Comput Appl Math 270 :557–563

U.S. Department of Energy, “Smart Grid / Department of Energy,” Web: http://www.energy.gov/oe/technology-development/smart-grid , Retrieved Sep. 23, 2015.

Fan W, Bifet A (2013) Mining big data: current status, and forecast to the future. ACM SIGKDD Explor Newsl 14(2):1–5

Al Nuaimi E, Al Neyadi H, Mohamed N, Al-Jaroodi J (2015) Applications of big data to smart cities. J Internet Serv Appl 6 (1):1–15

Plan SET (2015) Towards an integrated strategic energy technology (set) plan: accelerating the European energy system transformation. C 2015:6317

Wilson C, Hargreaves T, Hauxwell-Baldwin R (2017) Benefits and risks of smart home technologies. Energy Policy 103:72–83

Fabi V, Spigliantini G, Corgnati SP (2017) Insights on smart home concept and occupants’ interaction with building controls. Energy Procedia 111:759–769

Wilson C, Hargreaves T, Hauxwell-Baldwin R (2015) Smart homes and their users: a systematic analysis and key challenges. Personal Ubiquitous Comp 19(2):463–476

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Acknowledgements

I would like to express my very great appreciation to my professor for his valuable and constructive suggestions during the planning and development of this research work. His willingness to give his time so generously has been very much appreciated.

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Pira, S. The social issues of smart home: a review of four European cities’ experiences. Eur J Futures Res 9 , 3 (2021). https://doi.org/10.1186/s40309-021-00173-4

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Received : 11 April 2019

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DOI : https://doi.org/10.1186/s40309-021-00173-4

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