Mixed-dependency models for multi-resident activity recognition in smart homes
| العنوان: | Mixed-dependency models for multi-resident activity recognition in smart homes |
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| المؤلفون: | Qing Zhang, Tung-Son Ngo, Son N. Tran, Mohan Karunanithi |
| المصدر: | Multimedia Tools and Applications. 79:23445-23460 |
| بيانات النشر: | Springer Science and Business Media LLC, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Focus (computing), Dependency (UML), Computer Networks and Communications, business.industry, Computer science, Bayesian network, 020207 software engineering, 02 engineering and technology, Machine learning, computer.software_genre, Task (project management), Activity recognition, Hardware and Architecture, Home automation, 0202 electrical engineering, electronic engineering, information engineering, Media Technology, Artificial intelligence, Hidden Markov model, business, computer, Software |
| الوصف: | Recent growing interest in ambient intelligent environments has driven a desire for effective models to reason about activities of multiple residents. Such models are the keystone for the future of smart homes where occupants can be assisted with non-intrusive technologies. Much attention has been put on this research, however current works tend to focus on developing statistical algorithms for prediction, whilst there still lacks a study to fully understand the relations of residents’ behaviours and how they are reflected through the sensors’ states. In this paper we investigate the dependencies of the activities from residents and their interaction with the environments. We represent such dependencies in Bayesian networks that leads to construction of six variants of Hidden Markov Models (HMMs). Furthermore, we argue that a complete model should embody more than one type of dependency. Therefore, we propose an ensemble of HMMs, and then generalize it to a novel mixed-dependency model. In the experiments we perform intensive evaluation of our study on multi-resident activity recognition task. The results show that the proposed models outperform other models in three smart home environments, thus asserting our hypothesis. |
| تدمد: | 1573-7721 1380-7501 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::72f4d9974909d34b9b35505286bf60ec https://doi.org/10.1007/s11042-020-09093-0 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........72f4d9974909d34b9b35505286bf60ec |
| قاعدة البيانات: | OpenAIRE |
Find this article in full text from Springer Verlag. | تدمد: | 15737721 13807501 |
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