As aging populations grow and contribute to rising healthcare costs, policymakers and scholars recognize the need for technological solutions that reduce the costs of public service delivery. Smart ...homes, equipped with an array of physical and virtual networks, automated products, and intelligent system controls, present a cost-effective solution to extend the independence of older adults and persons with disabilities. We conduct a scoping review and reflexive thematic analysis of the existing literature on smart homes and healthcare. Our analysis of abstracts from 303 articles published between 2010 and 2020 finds that although the research on smart homes and health is nascent, there has been a marked growth in the last decade. The disciplines of study with the most prolific research on the health effects of smart home technology are health informatics, engineering & technology, nursing & medical, gerontechnology, computing, and wireless communications. Much of this research appears to be conducted in OECD countries. The major themes identified in the literature are supply-side topics focusing on the technological development of smart home systems and demand-side topics concentrating on primary, secondary, and tertiary users. Most of the research analyzed is a-theoretical and most empirical methodologies used involve quantitative methods.
Smart home assistants (SHAs) have gained a foothold in many households. Although SHAs have many beneficial capabilities, they also have characteristics that are colloquially described as creepy – a ...fact that may deter potential users from adopting and utilizing them. Previous research has examined SHAs neither from the perspective of resistance nor the perspective of creepiness. The present research addresses this gap and adopts a multi-method research design with four sequential studies. Study 1 serves as a pre-study and provides initial exploratory insights into the concept of creepiness in the context of SHAs. Study 2 focuses on developing a measurement instrument to assess perceived creepiness. Study 3 uses an online experiment to test the nomological validity of the construct of creepiness in a larger conceptual model. Study 4 further elucidates the underlying behavioral dynamics using focus group analysis. The findings contribute to the literature on the dark side of smart technology by analyzing the triggers and mechanisms underlying perceived creepiness as a novel inhibitor to SHAs. In addition, this study provides actionable design recommendations that allow practitioners to mitigate end users’ potential perceptions of creepiness associated with SHAs and similar smart technologies.
•Perceived creepiness is proposed as a novel inhibitor in the context of smart tech•A scale for measuring perceived creepiness is developed and validated•It is shown that SHAs can evoke perceptions of creepiness, leading to resistance•Transparency and tangibility are found as SHA design-side triggers of creepiness•Important mitigation options for practitioners in the design of SHAs are derived
The recent advancement and development of computer electronic devices has led to the adoption of smart home sensing systems, stimulating the demand for associated products and services. Accordingly, ...the increasingly large amount of data calls the machine learning (ML) field for automatic recognition of human behaviour. In this work, different deep learning (DL) models that learn to classify human activities were proposed. In particular, the long short-term memory (LSTM) was applied for modelling spatio-temporal sequences acquired by smart home sensors. Experimental results performed on the Center for Advanced Studies in Adaptive Systems datasets show that the proposed LSTM-based approaches outperform existing DL and ML methods, giving superior results compared to the existing literature.
Environmental sustainability is gathering further importance in various fields, including our homes. Smart home technologies are increasingly contributing to more efficient energy consumption, but ...their adoption rate remains lower than expected. This study proposes a theoretical model based on the extended unified theory of acceptance and use of technology (UTAUT2) to explore the effects of environmental awareness on individual intentions and behaviour toward smart home technologies. Data collected from 255 individuals were used to test the research model. The findings provide meaningful insights for researchers, marketers, and policymakers, by highlighting newer environmental approaches to these technologies.
•The various effects of environmental awareness on smart home adoption are explored.•Direct, mediating, and moderating effects of environmental awareness were found.•Environmental awareness has the strongest impact on intention to recommend.•Consumers' smart home adoption varies based on their environmental awareness levels.
•Sensor data contribution analysis method based on status frequency-inverse frequency.•Spatial distance matrix for context-awareness of cross-activities.•Novel wide time-domain convolutional neural ...network (WCNN, powerful parallel feature extraction).•The proposed method can save time and attain comparatively good performance.
With the development of artificial intelligence and the broad application of sensors, human activity recognition (HAR) technologies based on noninvasive environmental sensors have received extensive attention and have shown great application value. Owing to the initiative of human activities and machine learning-based methods relying on domain knowledge, obtaining a uniform model to understand the daily behaviors of different residents is difficult. From the perspective of data feature constraints to recognition methods, we constructed a methodology for single user's daily behavior recognition that can adaptively constrain the sensor noise during human activities in multitenant smart home scenarios. We propose a sensor data contribution significance analysis (CSA) method based on the sensor status frequency-inverse type frequency for HAR. This method is employed to measure the contribution of a particular type of sensor to a certain type of behavior recognition. We then build a spatial distance matrix based on the layout of environmental sensors for context-awareness and reducing data noise. Finally, we propose a HAR algorithm based on wide time-domain convolutional neural network and multienvironment sensor data (HAR_WCNN) for daily behavior recognition. Comparative experiment results on the CASAS dataset show that the proposed HAR_WCNN outperforms the compared state-of-the-art methods in terms of HAR accuracy and time consumption.
The Smart Home concept, associated with the pervasiveness of network coverage and embedded computing technologies is assuming an ever-growing significance for people living in the highly developed ...areas. However, the heterogeneity of devices, services, communication protocols, standards and data formats involved in most of the available solutions developed by different vendors, is adversely affecting its widespread application. In this paper, promoted by several promising opportunities provided by the advances in Internet of Things (IoT) and Cloud Computing technologies for facing these challenges, a novel multi-layer cloud architectural model is developed to enable effective and seamless interactions/interoperations on heterogeneous devices/services provided by different vendors in IoT-based smart home. In addition, to better solve the heterogeneity issues in the presented layered cloud platform, ontology has been used as a promising way to address data representation, knowledge, and application heterogeneity, and an ontology-based security service framework is designed for supporting security and privacy preservation in the process of interactions/interoperations. Challenges and directions for future work on smart home management have been also discussed at the end of this paper.
•A multi-layer cloud architectural model is developed to enable effective and seamless interactions/interoperations on heterogeneous devices/services provided by different vendors in IoT-based smart homes.•The ontology method has been used to better solve the heterogeneity issues in the presented layered cloud platform.•An ontology-based security service framework is designed for supporting security and privacy preservation in the process of interactions/interoperations.•Challenges and directions for future work on smart home management have been discussed.
In recent years, smart cities have emerged with energy conservation systems for managing energy in cities as well as buildings. Although many studies on energy conservation systems of smart homes ...have already been conducted, energy management at the city level is still a challenge due to the various building types and complex infrastructure. Therefore, this paper investigated the research themes on smart homes and cities through a quantitative review and identified barriers to the progression of smart homes to sustainable smart cities through a qualitative review. Based on the results of the holistic framework of each domain (smart home and city) and the techno-functional barriers, this study suggests that the following innovative solutions be suitably applied to advanced energy conservation systems in sustainable smart cities: (i) construction of infrastructure for advanced energy conservation systems, and (ii) adoption of a new strategy for energy trading in distributed energy systems. Especially, to reflect consumer behavior and energy in sustainable smart cities, the following responses to future research challenges according to the “bottom-up approach (smart home level to smart city level)” are proposed: (i) development of real-time energy monitoring, diagnostics and controlling technologies; (ii) application of intelligent energy management technologies; and (iii) implementation of integrated energy network technologies at the city level. This paper is expected to play a leading role as a knowledge-based systematic guide for future research on the implementation of energy conservation systems in sustainable smart cities.
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•In terms of energy technology, a connection between smart home and city is lacked.•Through quantitative review, research themes on smart home and city are identified.•Through qualitative review, barriers of progression to smart cities identified.•Bottom-up approach for energy conservation system in smart city is proposed.
•Designed a request handler mechanism to manage job requests of IoT devices.•Proposed PSO based resource scheduling technique for fog-assisted cloud environment.•Validated with the help of a case ...study of IoT based smart home automation.•Optimized QoS parameters such as response time, bandwidth, energy and latency.
There is a growing requirement for Internet of Things (IoT) infrastructure to ensure low response time to provision latency-sensitive real-time applications such as health monitoring, disaster management, and smart homes. Fog computing offers a means to provide such requirements, via a virtualized intermediate layer to provide data, computation, storage, and networking services between Cloud datacenters and end users. A key element within such Fog computing environments is resource management. While there are existing resource manager in Fog computing, they only focus on a subset of parameters important to Fog resource management encompassing system response time, network bandwidth, energy consumption and latency. To date no existing Fog resource manager considers these parameters simultaneously for decision making, which in the context of smart homes will become increasingly key. In this paper, we propose a novel resource management technique (ROUTER) for fog-enabled Cloud computing environments, which leverages Particle Swarm Optimization to optimize simultaneously. The approach is validated within an IoT-based smart home automation scenario, and evaluated within iFogSim toolkit driven by empirical models within a small-scale smart home experiment. Results demonstrate our approach results a reduction of 12% network bandwidth, 10% response time, 14% latency and 12.35% in energy consumption.
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A smart home is a residence equipped with smart technologies aimed at providing tailored services for users. Smart technologies make it possible to monitor, control and support residents, which can ...enhance the quality life and promote independent living. To facilitate the implementation and adoption of smart home technology it is important to examine the user's perspective and the current state of smart homes. Given the fast pace with which the literature has been developing in this area, there is a strong need to revisit the literature. The aim of this paper is to systematically review the smart home literature and survey the current state of play from the users' perspective. After discussing the systematic methodology, the review presents a comprehensive view of smart home definitions and characteristics. Then the study turns towards a discussion of the smart home types, related services and benefits. After outlining the current state of smart home benefits, the review discusses the challenges and barriers to smart home implementation. This review concludes by providing suggestions for future research.
•A literature review of smart homes from a user perspective•Systematic methodology adopted covering the period 2002 to 2017•Reviewed definitions, services, functions, and motivations for smart home adoption•Identified potential research gap related to smart homes
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