Having a clear understanding of what is home automation system and its role is essential for our research. We look carefully into different definitions, survey on current state of research in smart home area, technical and social barriers that prevent smart home to be adoptive in mass market (Risteska Stojkoska and Trivodaliev, 2017). Several practical architectures of HAS is also presented here in this section.
2.2.1 HAS - Definition, current features and its role in energy man-agement
Smart Home/Building have been studied and developed over the last three decades. Mul-tiple studies have been conducted to provide an adequate view of the definition of a smart home. (Toschi, Campos, and Cugnasca, 2017) surveyed to summarize the current state of the art of smart home automation and has pointed out several different definitions.
• “One which provides a productive and cost-effective environment through opti-mization of its four basic elements including structures, systems, services and man-agement” (Wigginton, 2013)
• “A smart home is a residence equipped with a high-tech network, linking sensors and domestic devices, appliances, and features that can be remotely monitored, accessed or controlled, and provide services that respond to the needs of its inhabi-tants” (Chan et al., 2009).
• (Buckman, Mayfield, and Beck, 2014) defines Smart Buildings as buildings which
“integrate and account for intelligence, enterprise, control, and materials and con-struction as an entire building system, with adaptability, not reactivity, at the core, in order to meet the drivers for building progression: energy and efficiency, longevity, and comfort and satisfaction”.
Definition from service/context-led perspective is another approach to identify home au-tomation (Reinisch et al., 2011). Although being expressed in different way, there is a substantial intersection among these definitions (Marikyan, Papagiannidis, and Ala-manos, 2019). Alternately, smart home should satisfy three main characteristics: internet of things, services and the ability to serve users’ need and comfort. User comfort is often expressed through air quality and thermal comfort management (Félix Iglesias Vázquez,
Kastner, and Kofler, 2013), together with the full control ability over the house. These re-quired characteristics are reflected understandably in HAS architecture that we are going to look into later on.
In summary, Smart Home/Building concept refers to all buildings in general, commercial or industrial buildings, apartment buildings, private houses. Although the terms Smart Buildings and Smart Home are used interchangeably from time to time, difference re-mains. Smart Buildings refer to significant economic buildings (e.g., office buildings, shopping mall) with shared facilities, HVAC systems, and multiple users. On the other hand, the term Smart Home may, in principle, indicate private housing or any form of residence, for example, standalone house or an apartment, where fewer users are inter-acting with the system in a personalized environment. Thus, a smart home is designed to be adaptive and user-centered. Within this study, to simplify the concept, we account for Smart Home or Home Automation System (HAS) in the scenario of a single user.
Smart homes are residential units substantially integrated with a communicating network of sensors and actuators centrally connected and monitored by intelligent systems. Ini-tially, HAS monitors the energy consumption of home appliances and automating the process of switching on/off devices to maximize energy usage efficiency. Recent years, emerging new technologies and artificial intelligence have matured to the point where systems are becoming more intelligent, and objects can even communicate to human (D’Souza et al., 2018; Sri Harsha, Chakrapani Reddy, and Prince Mary, 2017). Back-boned by smart systems, HAS embraced significant potentials towards achieving comfort, security, independent lifestyle, enhanced quality of life while taking into account envi-ronmental impact. Smart home energy efficiency services assist homeowners in reducing energy demand, whether directly (through automated energy-saving mechanisms, such as lowering the heating on hot sunny days) or indirectly (e.g., by providing the user with centralized access to data about their real-time energy usage and energy bill) (Farmani et al., 2018).
Technologies rising provides opportunities for energy management features to be feasi-ble, however, according to the view of (Ford et al., 2017), it’s not clear whether these technologies are effective, as the field new and it is still currently being developed, and how well those can help managing energy usage with efficiency. The analysis of (ibid.) explores the range of smart home technologies currently available in the market and their mature level in practical application. While more and more technologies are available,
choosing which tools to use depends greatly on the engineers point of view, usually sub-jectively. The variety of smart home ecosystem also effect its ability to actually efficiently manage energy consumption (Demeure et al., 2015), for better or worse.
When put in connection with other surrounding fields, HAS plays a role of an enabler.
Supporting those with disabilities with an accessible environment encourage development of assistive technologies. Wearable devices are in favor to provide more user contextual data, especially helpful in healthcare services. Developed in Japan, LifeMinder - a "wear-able health care assistant" - is an example of application of smart technologies in health care (Chan et al., 2009; Suzuki and Doi, 2001). Smart homes and health-care start to share some interest in common and future perspective on smart home systems can evolve as a home-based health care system (Chan et al., 2009).
From a user perspective, future of smart homes will involve more in user-related benefits such as assistive environment and health-care supportive applications. Current tendency in smart homes research is mainly about location-based recognition (Mainetti, Mighali, and Patrono, 2015), cloud based and smart phone supportive scalable system (Korkmaz et al., 2015), activity recognition and modeling user behaviors with the help of machine learning algorithms (Bouchard et al., 2018; Aipperspach, Cohen, and Canny, 2010; Roy et al., 2010), or knowledge-driven approach (Chen, Nugent, and Wang, 2012).
Apart from smart homes features study, interaction with the system is worth paying at-tention. Although possibility to remote control of smart homes is known widely as the main interaction method via traditional controller, there exists other possibilities. Several studies focus on voice command recognition (Principi et al., 2015), improving voice-based control of smart homes (Chahuara, Portet, and Vacher, 2017). The idea of (Prin-cipi et al., 2015) is that acoustic signals provide handy way to monitor user activity and they also enable hand-free human-to-machine interaction. Voice-based command systems have gained popularity. (Villanueva and P. O. Droegehorn, 2018) has conducted a study into using gesture to interact with home automation, expanding the sphere of human-machine interaction. The release of gesture recognition technologies - the LEAP Motion Controller - opened new frontiers for interacting with ICT system in different means.
2.2.2 HAS - key challenges and social barriers
Smart homes enable users to be able to control home appliances even when they are away and provide with an opportunity to save energy costs. (Marikyan, Papagiannidis, and Ala-manos, 2019) reviews the potentials and benefits of HAS adoption and categorizes them by different aspects, for example, by health-related matters, by environmental benefits or affection on financial and psychological well-being benefits. Despite its benefits and increasing popularity, there are numerous challenges in the acceptance of smart homes by society. (Balta-Ozkan et al., 2013) summarizes the important barriers of smart home adoption into seven categories:
• The ability to adapt to user lifestyle where familiar behaviors need to be fitted.
• Administration matter.
• Interoperability between different smart home devices that may be made by differ-ent manufacturers.
• Reliability of the system.
• Privacy and security matters.
• Trustworthiness of the system.
• Installing and maintenance costs.
We review each of the categories and analyze the causes of barriers. (Marikyan, Papa-giannidis, and Alamanos, 2019) generalize these areas into three main groups of causes:
technological issues, reasons involving financial (e.g., price of devices, installation cost), ethical matters (e.g., misuse of user data, conflict of interest between HAS providers and users), legal concerns (e.g., regulations to protect user data, lack of legal means and in-structions). Knowledge gap and psychological resistance are also considered to be the reason of the refusal towards HAS widely adoption.
(Shuhaiber and Mashal, 2019) reviewed factors that influence residents’ acceptance and usage of smart home by examining users’ personal factors (e.g., awareness and trust) on smart homes acceptance and intention to use it. The study findings show that users’ atti-tude towards accepting HAS is connected to the users’ awareness, perceived enjoyment and trust. Another study held by (Shin, Park, and D. Lee, 2018) found that compatibility and perceived ease of use had positive effects on purchase intention. However, as the number of including smart homes increases speedily, personal information is becoming more and more critical to be taken care of.
In our research, we focus on HAS fit to the user’s home, current and changing lifestyle.
From one side, smart home appliances should be ubiquitous and fit to the home design and environment. However, most importantly the HAS must fit with general routines of home owners. One of the evolving areas of integrating user routines into HAS is the context-aware computing approach (Hong, Li, and Jingxiao, 2013; Youngjae Kim and Dongman Lee, 2008). The context-driven applications consider user’s current situation to provide relevant services. The next section provides definition of context-aware systems and review existing context-enriched HAS.
2.2.3 HAS - Architecture
A typical smart home architecture is composed of four components (Balta-Ozkan et al., 2013): underlying communication infrastructure; smart command and management; a connected sensor network around the house; and automation services. Smart home ser-vices are the benefits that the smart home provides to the user (for example, the ability to manage demand, the mean to remotely control the house and connected devices or auto-mated actions that will be executed based on, mostly, fixed predefined schedule), which is enabled by the smart home’s network of connected physical components and network infrastructure. Services may be categorized according to the user’s needs they target, e.g., security, health, assisted the living, communication and entertainment, convenience and comfort, and finally, energy efficiency (ibid.).
Figure 1shows the CASAS architecture – a project conducted by Washington State Uni-versity. This architecture (Cook et al., 2013) facilitates the development and implemen-tation of future smart home technologies by offering an easy-to-install lightweight design that provides smart home capabilities out of the box with no customization or training.
Sensors implanted around the home read data on the surrounding environment and trans-fer to a central controller. Data from sensors is the input of intelligent-based systems (e.g., activity recognition, action discovery, positioning service). Any reaction to the HAS or information will be transferred back to the user through this network, controlled by the central manager.
A location-aware architecture for heterogeneous Building Automation Systems proposed by (Mainetti, Mighali, and Patrono, 2015) also follows the design principles of HAS. The architecture in Figure 2 can be divided into three major components following a HAS characteristics. At the foundation is a network infrastructure with smart devices possibly
Figure 1:CASAS smart home architecture overview.
Source: CASAS: A Smart Home in a Box (Cook et al., 2013)
connected by various protocols (Bluetooth, RFid, Wifi). On top of this foundation is the management unit where they implement business logic specified by user. And an application layer with user interface allowing user to interact with the system. These designate choices allow for the scalability and flexibility of the HAS.