Users’ Preferences for Smart Home Automation – Investigating Aspects of Privacy and Trust

Smart Home Advancements for Health Care and Beyond: Systematic Review of Two Decades of User-Centric Innovation

BACKGROUND

The rapid advancement of Internet of Things and artificial intelligence technologies has driven significant growth in the demand for smart home products, with household penetration projected to increase from 77.6% in 2025 to 92.5% in 2029. Despite this growth, much of the existing research adopts a technology-push approach, focusing primarily on user adoption and acceptance from the perspective of technology providers rather than addressing the evolving needs and experiences of users.

OBJECTIVE

This study seeks to bridge this gap by conducting a comprehensive review of 20 years of smart home literature (2000-2023) using bibliometric and thematic analysis. The objective is to align future research with user needs and market trends by examining technology, user behavior, and service perspectives to inform academic and industry developments.

METHODS

The analysis was carried out in four steps: (1) collecting 5981 abstracts from the Web of Science database (from 2000 to the first half of 2023), (2) preprocessing and refining the data, (3) applying topic modeling to 1003 selected papers, and (4) combining bibliometric network analysis with qualitative, in-depth interpretation.

RESULTS

This study identified 110 key topics across 4 distinct periods, providing insights into 2 decades of advancements in technology, applications, and user-centered research. The findings illustrate the progression of smart home technologies from wireless networks to Internet of Things and artificial intelligence, the expansion of services from basic monitoring to applications such as energy management and health care, and a shift in user profiles from early adopters to underserved populations. The study highlights the limitations of the technology-push approach and underscores the importance of understanding diverse user groups and improving user experiences. It also emphasizes the potential of ambient intelligence environments to intuitively adapt to the health and lifestyle needs of all residents, simplifying and enriching daily life.

CONCLUSIONS

This research delivers valuable academic and practical insights into the evolution of the smart home domain, showcasing a shift from technology-push strategies to user-centered approaches. By prioritizing user satisfaction and quality of life-especially in health care-the findings open new commercial opportunities and pave the way for innovative, real-world smart home solutions tailored to contemporary user needs.

Detecting Older Adults' Behavior Changes During Adverse External Events Using Ambient Sensing: Longitudinal Observational Study

Background

Older adults manage multiple impacts on health, including chronic conditions and adverse external events. Smart homes are positioned to have a positive impact on older adults' health by (1) allowing new understandings of behavior change so risks associated with external events can be assessed, (2) quantifying the impact of social determinants on health, and (3) designing interventions that respond appropriately to detected behavior changes. Information derived from smart home sensors can provide objective data about behavior changes to support a learning health care system. In this paper, we introduce a smart home capable of detecting behavior changes that occur during adverse external events like pandemics and wildfires.

Objective

Examine digital markers collected before and during 2 events (the COVID-19 pandemic and wildfires) to determine whether clinically relevant behavior changes can be observed and targeted upstream interventions suggested.

Methods

Secondary analysis of historic ambient sensor data collected on 39 adults managing one or more chronic conditions was performed. Interrupted time series analysis was used to extract behavior markers related to external events. Comparisons were made to examine differences between exposures using machine learning classifiers.

Results

Behavior changes were detected for 2 adverse external events (the COVID-19 pandemic and wildfire smoke) initially and over time. However, the direction and magnitude of change differed between participants and events. Significant pandemic-related behavior changes ranked by impact included a decrease in time (3.8 hours/day) spent out of home, an increase in restless sleep (946.74%), and a decrease in indoor activity (38.89%). Although participants exhibited less restless sleep during exposure to wildfire smoke (120%), they also decreased their indoor activity (114.29%). Sleep duration trended downward during the pandemic shutdown. Time out of home and sleep duration gradually decreased while exposed to wildfire smoke. Behavior trends differed across exposures. In total, two key discoveries were made: (1) using retrospective analysis, the smart home was capable of detecting behavior changes related to 2 external events; and (2) older adults' sleep efficiency, time out of home, and overall activity levels changed while experiencing external events. These behavior markers can inform future sensor-based monitoring research and clinical application.

Conclusions

Sensor-based findings could support individualized interventions aimed at sustaining the health of older adults during events like pandemics and wildfires. Creating care plans that directly respond to sensor-derived health information, like adding guided indoor exercise, web-based socialization sessions, and mental health-promoting activities, would have practical impacts on wellness. The smart home's novel, evidence-based information could inform future management of chronic conditions, allowing nurses to understand patients' health-related behaviors between the care points so timely, individualized interventions are possible.

Navigating the crossroads of aging, caregiving and technology: Insights from a southern Spain about video-based technology in the care context

Objective

As the world faces an aging population, the complexities of care management become increasingly pronounced. While technological solutions hold promise in addressing the dynamic demands of care, many nuances are to be considered in the design and implementation of active and assisted living technologies (AAL) for older adult care. This qualitative study, set in southern Spain, is positioned at the crossroads of healthcare challenges, as seen by the different actors involved in the care process and the technological solutions developed in response to these challenges. By investigating the complex landscape of caregiving and by examining the experiences and challenges faced by caregivers, healthcare professionals, and older adults, we aim to guide the development of vision-based AAL technologies that are responsive to the genuine needs of older adults and those requiring care.

Methods

A qualitative research methodology was used in the study. In total15 in-depth interviews and five focus groups were conducted with a diverse group of stakeholders involved in the process of care provision and reception.

Results

While the results demonstrate that there is a readiness for technological solutions, concerns over privacy and trust highlight the need for a carefully integrated, human-centric approach to technology in caregiving.

Conclusion

This research serves as a compass, guiding future discussions on the intersection of aging, technology, and care, with the ultimate goal of transforming caregiving into a collaborative and enriching journey for all stakeholders involved.

An empirical analysis of the factors driving customers' purchase intention of green smart home products

With the improvement of consumers' environmental awareness and the popularity of the Internet of Things, green smart home products (GSHPs) are becoming the dominant trend of future home life. This shift not only makes tedious home life easier and more convenient but also helps families save energy and reduce carbon emissions. However, given the impact of the current technological level, the proportion of users who actually purchase GSHPs remains small. Thus, seeking ways to promote the consumption of GSHPs has become an urgent issue. Hence, this study seeks to fill the gap in the existing research on green consumption behavior and obtain a full understanding of the factors influencing the purchase intention of GSHPs. To do so, this work uses task-technology fit theory and considers the actual situation of green smart home consumption to add social-technology fit into the original theoretical basis. In particular, this research focuses on middle- and high-end Chinese consumers who have experience in purchasing GSHPs. Moreover, it aims for an in-depth exploration of the formation mechanism of Chinese consumers' purchase intention for GSHPs through structural equation modeling. Using survey data collected from 331 green smart home product users in China, the study empirically examines the relationships among autonomy, environmental agility, sense of belonging, and self-actualization, and both task-technology fit and social-technology fit, which are expected to shape the purchase intention of GSHP users. The empirical results provide broad support for our hypotheses. The results of this study offer important contributions to the increasing research on GSHPs consumption and shed light on the importance of both technology characteristics and the needs of users in achieving both task-technology fit and social-technology fit and, ultimately enhancing the users' intention to purchase GSHPs.

Factors that predict the acceptance and adoption of smart home technology by seniors in Australia: a structural equation model with longitudinal data

Smart Home Technology presents an exciting opportunity to support seniors living independently in their homes. Despite widespread interest in Smart Homes, seniors' readiness to adopt Smart Home Technology is low. To determine the factors underpinning Australian seniors' acceptance and adoption of Smart Home Technology using an extended UTAUT model that includes Trust, Resistance to Change and Technology Anxiety. A longitudinal study was conducted to validate the proposed model prior to and after the implementation of a pilot Smart Home Modification program for seniors. Structural Equation Modeling has been applied to test the proposed hypotheses using a sample of 60 seniors in regional Australia. Perceived Usefulness is an important predictor of Smart Home Technology adoption by seniors. Trust was found to indirectly predict adoption of Smart Home Technology via Perceived Usefulness. This study showed that Perceived Usefulness and Trust are critical factors for the acceptance and use of SHT by seniors, validating the extension of UTAUT with a Trust factor. This makes a unique theoretical contribution to the literature with implications for aged care providers and policymakers to consider seniors' perceived usefulness and trust in the design, development, and implementation of Smart Home solutions.

An Anonymous Authentication and Key Update Mechanism for IoT Devices Based on EnOcean Protocol

EnOcean, a commonly used control protocol in smart lighting systems, provides authentication, as well as message integrity verification services, and can resist replay attack and tamper attack. However, since the device identity information transmitted between sensors in smart lighting control systems is easily accessible by malicious attackers, attackers can analyze users' habits based on the intercepted information. This paper analyzed the security of the EnOcean protocol using a formal analysis method based on the colored Petri net (CPN) theory and the Dolev-Yao attacker model and found that the protocol did not anonymize the device identity information and did not have a communication key update mechanism, so an attacker could easily initiate a key compromise impersonation attack (KCIA) after breaking the pre-shared communication key. To address the above security issues, this paper proposed an EnOcean-A protocol with higher security based on the EnOcean protocol. The EnOcean-A protocol introduced a trusted third-party server to send communication keys to communication devices because devices must obtain different communication keys from the trusted third-party server each time they communicated. Thus, this protocol could resist a KCIA and achieve forward security. Meanwhile, the device identity information was anonymized using a homomorphic hash function in the EnOcean-A protocol, and the dynamic update mechanism of the device identity information was added so that an attacker could not obtain the real identity information of the device. Finally, the formal analysis of the EnOcean-A protocol showed that the new protocol could resist a KCIA and ensure the anonymity and untraceability of the communication device, which had higher security compared with the EnOcean protocol.

Identifying the Key Drivers and Barriers of Smart Home Adoption: A Thematic Analysis from the Business Perspective

Smart homes embrace advanced technologies and the connectedness of devices that aim to increase consumers’ life quality. They are based on data integration over shared platforms collected via sensors and wireless networks. However, although consumers’ current and potential adoption of smart homes have received some research interest, there is a low number of studies considering the foreseeable future of smart homes from the business perspective. To fulfill this gap in the literature, this study presents the results of an exploratory research attempting to reveal the foresight of the business side regarding the penetration of smart home technologies (SHTs) into consumers’ lives. Based on the opinions of industry experts collected through 13 semistructured in-depth interviews, numerous drivers of and barriers to SHT adoption are uncovered and displayed in their intertwined relationship in a thematic map. In creating this map, the qualitative data gathered through the interviews are integrated with widely used theories/models of technology adoption in the literature to develop a full-fledged set of determinants. As a result, drivers of SHT adoption (five sub-themes) and barriers that hinder smart home penetration (eight subthemes) were determined. Drivers consist of relative advantage, enjoyment, image enhancement, modern and multifunctional design, and consumers’ technology innovativeness. In contrast, the main barriers are high cost, complexity, lack of compatibility, lack of trialability, lack of observability, lack of a trusted brand in the market, lack of facilitating conditions and support services, and consumers’ technology anxiety. This rich set of SHT adoption determinants can be used in future studies to examine their relative impact on consumers’ adoption of SHT.

Smart energy systems beyond the age of COVID-19: Towards a new order of monitoring, disciplining and sanctioning energy behavior?

The Corona pandemic has led to the increased use of online tools throughout society, whether in business, education, or daily life. This shift to an online society has led social scientists to question the extent to which increased forms of control, surveillance and enforced conformity to ways of thinking, attitudes and behaviors can be promoted through online activities. This question arises overtly amidst a pandemic, but it also lurks behind the widespread diffusion of smart energy systems throughout the world and the increased use of smart meters in those systems. The extent to which forms of monitoring, disciplining and sanctioning of energy behavior and practices could come to reality is thus an important question to consider. This article does so using the ideas of Michel Foucault, together with research on smart energy systems and current trends in energy policy. The article closes with a discussion of energy democracy and democratic legitimacy in the context of possible effects of smart technologies on community energy systems.