Management of Uncertainty and Spatio-Temporal Aspects for Monitoring and Diagnosis in a Smart Home

Empirical Examination of Intention to Continue to Use Smart Home Services

With the continuous expansion of sub-ecological problems, it is the question of how to effectively reduce environmental pollution and improve energy efficiency that has become a major challenge. At the same time, the energy consumption of family homes accounts for a large proportion, and whether smart homes can become a part of sustainable development is getting more and more attention. Although there are hundreds of smart home products and many investors on the market, consumers are relatively less accepting of this technology. How to make consumers adopt and continue to use has become a key issue in the development of smart homes. From the perspective of consumers, this study aims first to explore the relevant factors that affect the sustainable use of smart homes, and second empirically analyze the hypothetical model by using structural equation modeling. The empirical analysis results are based on the sample data of 488 Chinese respondents with experience in smart home use. The results showed that the service quality and perceived usefulness of smart home services positively impact users’ degree of satisfaction, and a higher degree of satisfaction, in turn, contributes to users’ formation of habits. Users’ desire to continuously use smart home services is influenced by perceived usefulness, degree of satisfaction, and habit; among them, habit is the key factor affecting users’ willingness. These findings expand our understanding of users’ desire to continuously use smart homes and provide theoretical support for the sustainable development of the smart home industry.

Surveying Human Habit Modeling and Mining Techniques in Smart Spaces

A smart space is an environment, mainly equipped with Internet-of-Things (IoT) technologies, able to provide services to humans, helping them to perform daily tasks by monitoring the space and autonomously executing actions, giving suggestions and sending alarms. Approaches suggested in the literature may differ in terms of required facilities, possible applications, amount of human intervention required, ability to support multiple users at the same time adapting to changing needs. In this paper, we propose a Systematic Literature Review (SLR) that classifies most influential approaches in the area of smart spaces according to a set of dimensions identified by answering a set of research questions. These dimensions allow to choose a specific method or approach according to available sensors, amount of labeled data, need for visual analysis, requirements in terms of enactment and decision-making on the environment. Additionally, the paper identifies a set of challenges to be addressed by future research in the field.

Resolving conflicts in knowledge for ambient intelligence

Ambient intelligence (AmI) proposes pervasive information systems composed of autonomous agents embedded within the environment who, in orchestration, complement human activity in an intelligent manner. As such, it is an interesting and challenging application area for many computer science fields and approaches. A critical issue in such application scenarios is that the agents must be able to acquire, exchange, and evaluate knowledge about the environment, its users, and their activities. Knowledge populated between the agents in such systems may be contextually dependent, ambiguous, and incomplete. Conflicts may thus naturally arise, that need to be dealt with by the agents in an autonomous way. In this survey, we relate AmI to the area of knowledge representation and reasoning (KR), where conflict resolution has been studied for a long time. We take a look at a number of KR approaches that may be applied: context modelling, multi-context systems, belief revision, ontology evolution and debugging, argumentation, preferences, and paraconsistent reasoning. Our main goal is to describe the state of the art in these fields, and to draw attention of researchers to important theoretical issues and practical challenges that still need to be resolved, in order to reuse the results from KR in AmI systems or similar complex and demanding applications.

Literature review on monitoring technologies and their outcomes in independently living elderly people

PURPOSE

To obtain insight into what kind of monitoring technologies exist to monitor activity in-home, what the characteristics and aims of applying these technologies are, what kind of research has been conducted on their effects and what kind of outcomes are reported.

METHODS

A systematic document search was conducted within the scientific databases Pubmed, Embase, Cochrane, PsycINFO and Cinahl, complemented by Google Scholar. Documents were included in this review if they reported on monitoring technologies that detect activities of daily living (ADL) or significant events, e.g. falls, of elderly people in-home, with the aim of prolonging independent living.

RESULTS

Five main types of monitoring technologies were identified: PIR motion sensors, body-worn sensors, pressure sensors, video monitoring and sound recognition. In addition, multicomponent technologies and smart home technologies were identified. Research into the use of monitoring technologies is widespread, but in its infancy, consisting mainly of small-scale studies and including few longitudinal studies.

CONCLUSIONS

Monitoring technology is a promising field, with applications to the long-term care of elderly persons. However, monitoring technologies have to be brought to the next level, with longitudinal studies that evaluate their (cost-) effectiveness to demonstrate the potential to prolong independent living of elderly persons. [Box: see text].