Factors Influencing Consumer Adoption of Smart Home Systems: A Socio-Demographic Perspective

The age group of 65 years has been described as the fastest growing demographic in the world. As life expectancy increases, older adults prefer to remain independent at home. Smart Home systems and Assistive Technologies have been developed to enable older adults to live in their own homes as they age, enhancing safety, independence and quality of life. Although considerable Smart Home mobile applications exist focused on older adult’s wellbeing, they still face considerable challenges in usability, feasibility and accessibility regarding design of interfaces. There is a gap in recent research on evaluation of User Interface (UI) designed or adapted to address older adults needs and abilities. The paper takes part of an ongoing project evaluation stage, for a smart home and health monitoring system, applied in two stages: (i) heuristic evaluation and (ii) remote user testing. The main objective of the paper is to focus on the second evaluation stage, that took place with end users, applying unmoderated remote usability testing, due to Covid-19 pandemic. According to the System Usability Scale (SUS) and Net Promoter Score (NPS) techniques it could be able to quantify the users experience and measure the level of satisfaction related to the smart home and health monitoring system. The SUS results identified that the system’s usability was considered acceptable with a final score of 65,6. It was concluded that the unmoderated test with a SUS post-questionnaire can be a complex method to apply with older adults. The SUS questionnaire could lead to mistakes and misinterpretation, some contradictory results could be related to this complexity among older adults, and this could lead to a major impact on overall SUS scores. In addition, the NPS metric was identified as not the appropriate to measure user satisfaction with a small sample of users as SUS technique. It is concluded that findings should be supported by applying individual moderated tests with more end users to provide insights to designers and developers to create more usable interfaces to address the needs and abilities of the older adults.KeywordsSmart homeAge-friendly designUser interface designRemote user testing

<p>This paper examines the integration of smart home and solar panel system that is controlled and monitored using IoT (internet ofthings). To enable the smart home system to monitor the activity within the house and act according to the current conditions, it is equipped with several sensors, actuators and smart appliances. All of these devices have to be connected to a communication network, so they can communicate and provide services forthe smart home’s in habitants. The smart home system was first introduced to provide comfort and convenience, but later it should also address many other things, e.g. the importance of the efficient use of energy or electricity and hybrid use of energy sources. A solar panel is added to the smart home prototype and its addition is studied. Adaptive linear neural network is implemented in the prototype as an algorithm for predicting decisions based on the current conditions. The construction of the proposed integrated systemis carried out through several procedures, i.e. the implementation of the adaptive linear neural network (ADALINE) as the neural network method, the design of the prototype and the testing process. This prototype integrates functionalities of several household appliances into one application controlled by an Android-based framework.</p>

Embedded Smart Home System Based on ZigBee

With the rapid development of the Internet of Things and artificial intelligence technology, the smart home system has become an important part of the modern living environment. Human-Computer Interaction (HCI), is a key factor of smart home user experience, the optimization of its mode and attributes is crucial to improve user satisfaction. Smart home system provides a convenient life experience, but the complex interaction mode and unclear interaction attributes may lead to user operation difficulties and affect user acceptance. Therefore, a further study of the mode and attributes of HCI is of great significance for the design of a more humanized intelligent home system. The purpose of this study is to explore the variables related to the characteristics and attributes of HCI in the existing smart homes. The key variables are extracted through an extensive literature review, collecting and organizing existing relevant studies of smart home HCI characteristics and attributes. A comprehensive framework of HCI characteristics is constructed based on the literature findings while the interactions are revealed through the constructed model towards theoretical support and practical guidance for future smart home design. The findings will help smart home developers and designers gain a deeper understanding of user needs in designing a more efficient, intuitive, and satisfactory smart home interaction system.

Topicality. Smart home systems are becoming increasingly popular as they offer homeowners many benefits, such as increased convenience, energy efficiency, and improved security. However, these systems can also pose potential security risks if not properly secured. Detecting threats in a smart home system is crucial for protecting personal data, preventing physical security breaches and cyberattacks, and ensuring the proper functioning of the system. The article examines the assessment of the most dangerous threats to the cyber-physical system of a smart home. The process was carried out by conducting an in-depth examination based on a wide list of threats, taking into account their impact on security services. All threats were identified according to their source according to the concept of double-circuit security. The subject of the article is the methods of expert assessment of critical security threats in cyber-physical systems of a smart home. The purpose of the study is to identify and classify the most dangerous security threats to cyber-physical systems of a smart home based on expert assessment. As a results, the most critical threats to cyber-physical systems of a smart home were identified and the basis for developing algorithms for their effective prevention was formed. Conclusions. As a result of the expert assessment, the most critical threats to cyber-physical systems of a smart home were identified, which creates the basis for developing effective methods for their prevention and risk minimization.

The introduction of modern Smart Home Systems (SHSs) is redefining the way we perform everyday activities. Today, myriad SHS applications and the devices they control are widely available to users. Specifically, users can easily download and install the apps from vendor-specific app markets, or develop their own, to effectively implement their SHS solutions. However, despite their benefits, app-based SHSs unfold diverse security risks. Several attacks have already been reported to SHSs and current security solutions only consider smart home devices and apps individually to detect malicious actions, rather than the context of the SHS as a whole. Thus, the current security solutions applied to SHSs cannot capture user activities and sensor-device-user interactions in a holistic fashion. To address these limitations, in this article, we introduce A egis +, a novel context-aware platform-independent security framework to detect malicious behavior in an SHS. Specifically, A egis + observes the states of the connected smart home entities (sensors and devices) for different user activities and usage patterns in an SHS and builds a contextual model to differentiate between malicious and benign behavior. We evaluated the efficacy and performance of A egis + in multiple smart home settings (i.e., single bedroom, double bedroom, duplex) and platforms (i.e., Samsung SmartThings, Amazon Alexa) where real users perform day-to-day activities using real SHS devices. We also measured the performance of A egis + against five different malicious behaviors. Our detailed evaluation shows that A egis + can detect malicious behavior in SHS with high accuracy (over 95%) and secure the SHS regardless of the smart home layout and platforms, device configurations, installed apps, controller devices, and enforced user policies. Finally, A egis + yields minimum overhead to the SHS, ensuring effective deployability in real-life smart environments.

Our everyday lives are expanding fast with the introduction of new Smart Home Systems (SHSs). Today, a myriad of SHS devices and applications are widely available to users and have already started to re-define our modern lives. Smart home users utilize the apps to control and automate such devices. Users can develop their own apps or easily download and install them from vendor-specific app markets. App-based SHSs offer many tangible benefits to our lives, but also unfold diverse security risks. Several attacks have already been reported for SHSs. However, current security solutions consider smart home devices and apps individually to detect malicious actions rather than the context of the SHS as a whole. The existing mechanisms cannot capture user activities and sensor-device-user interactions in a holistic fashion. To address these issues, in this paper, we introduce Aegis, a novel context-aware security framework to detect malicious behavior in a SHS. Specifically, Aegis observes the states of the connected smart home entities (sensors and devices) for different user activities and usage patterns in a SHS and builds a contextual model to differentiate between malicious and benign behavior. We evaluated the efficacy and performance of Aegis in multiple smart home settings (i.e., single bedroom, double bedroom, duplex) with real-life users performing day-to-day activities and real SHS devices. We also measured the performance of Aegis against five different malicious behaviors. Our detailed evaluation shows that Aegis can detect malicious behavior in SHS with high accuracy (over 95%) and secure the SHS regardless of the smart home layout, device configuration, installed apps, and enforced user policies. Finally, Aegis achieves minimum overhead in detecting malicious behavior in SHS, ensuring easy deployability in real-life smart environments.

One of the most commonly used methods for accessing sensors and control points in smart home systems is communication via Radio Frequency (RF) waves. Even in newly constructed buildings, the most suitable method is to mount RF sensors and controllers. With current developments in cloud-based smart home and intercom systems, the software of the systems is also updated via an update server. But some updates may also be needed in RF sensors and controllers that are part of the system. Due to their cheap and simple structures, these devices developed with embedded software usually need to be removed from their places or reprogrammed with special devices by physical contact in order to update their software. But RF devices are often not easy to access. They are usually hidden in places such as behind sockets or junction boxes. In order to update their program remotely without removing them, a protocol has been developed between RF modules and in-apartment monitors/gateways and appropriate software has been written.

Verifying trust over IoT-ad hoc network-based applications under uncertainty

With the continuous development of the social economy, people from all walks of life attach great importance to the smart home design of artificial intelligence technology. In the context of the information age, people’s requirements for the quality of life are also gradually upgrading, and the requirements for home furnishing have also been upgraded from the traditional requirements of only living places to the expectation that a more intelligent, convenient, smart home has gradually been brought into life by people. The smart home system can integrate all control terminals into one system and implement on-site or remote control of home equipment using the computer terminal and mobile phone terminal, to realize the function of managing home equipment more conveniently and flexibly. Artificial intelligence technology as one of the important links adopts a structured design scheme to control and complete the design of the smart home system. Compared with most smart home systems on the market, this system also focuses on the safety precautions of the residential environment. It adopts infrared detectors for doors and windows and gravity sensing devices for indoor floors. The space-time barriers between home systems optimize and enhance the user’s living experience. The article first analyzes the architecture, mainstream technology, and characteristics of computer technology and then discusses the design and implementation of my country’s smart home system, providing strong support for subsequent research.

Environmental saving potentials of a smart home system from a life cycle perspective: How green is the smart home?

Past few decades have seen a sharp increase in air pollution and its harmful effects on human health. Indoor air quality is a major determining factor of personal exposure to pollutants in today's scenario. Major time is spent in indoor environments by a majority of people. Therefore monitoring indoor air quality has become an important issue. There are various reasons for poor quality of indoor air in which the oxygen level is below the healthy level such as influx of polluted outdoor air, geological materials around the residential properties, household activities such as cooking, cleaning, smoking, materials used in construction or painting the house etc. With increasing pollution, the respiratory diseases are on the rise and therefore there is a strong need to develop a smart home system which is capable to monitor healthy environmental conditions for its users. This research study proposes a smart system that uses a renewable source of energy, monitors and controls the overall power consumption of the home, and keeps a check on the healthy environmental conditions by measuring the level of oxygen and provides a provision for an alarm when the oxygen level falls below the safe limit. The proposed model is compact, cost-effective, energy-efficient and provides a health-smart home system to the consumer and is especially useful for the old and physically challenged.

Past few decades have seen a sharp increase in air pollution and its harmful effects on human health. Indoor air quality is a major determining factor of personal exposure to pollutants in today's scenario. Major time is spent in indoor environments by a majority of people. Therefore monitoring indoor air quality has become an important issue. There are various reasons for poor quality of indoor air in which the oxygen level is below the healthy level such as influx of polluted outdoor air, geological materials around the residential properties, household activities such as cooking, cleaning, smoking, materials used in construction or painting the house etc. With increasing pollution, the respiratory diseases are on the rise and therefore there is a strong need to develop a smart home system which is capable to monitor healthy environmental conditions for its users. This research study proposes a smart system that uses a renewable source of energy, monitors and controls the overall power consumption of the home, and keeps a check on the healthy environmental conditions by measuring the level of oxygen and provides a provision for an alarm when the oxygen level falls below the safe limit. The proposed model is compact, cost-effective, energy-efficient and provides a health-smart home system to the consumer and is especially useful for the old and physically challenged.

Prototype, method, and experiment for evaluating usability of smart home user interfaces

Smart home systems are featured by a variety of connected smart household devices, where Internet of Things (IoT) is one of the critical enablers in the smart home environment. Since these smart home IoT devices are working collaboratively, the access control among the IoT devices becomes more and more important because non-authorised access can result in resource misuse, home breach threats or private information disclosure. Thus, an effective access control in smart home systems is essential to prevent from unauthorized use of the available resources. However, most of the access control schemes in smart home systems are still lack of decentralized peer trust and hard to control the security and credibility of the smart home IoT network. This paper therefore proposes a Blockchain-based Access Control (BAC) solution by integrating the Blockchain technique to IoT networks, where the agent-based policy is proposed to improve the efficiency of the Blockchain management. In order to validate the BAC solution, we demonstrate the implementation process of the proposed BAC in the parental control scenario and also evaluate performance and feasibility in a simulated smart home.