ArticleSensors (Basel, Switzerland)2016
A Semantic Approach with Decision Support for Safety Service in Smart Home Management.
Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Non-Invasive Ambient Intelligence in Real Life: Dealing with Noisy Patterns to Help Older People.Sensors (Basel, Switzerland) · 2019Article
- Artificial Intelligence-Based Semantic Internet of Things in a User-Centric Smart City.Sensors (Basel, Switzerland) · 2018Article
- Ontology-Based Method for Fault Diagnosis of Loaders.Sensors (Basel, Switzerland) · 2018Article
- A Survey of Data Semantization in Internet of Things.Sensors (Basel, Switzerland) · 2018Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.
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Registered trials
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