Jheng-Jhe Sie, Shang-Chen Yang, Zih-Yun Hong, Chien-Kai Liu, Jen-Jee Chen, S. C. Li
{"title":"整合云计算、物联网和社区,支持长期护理和失散老人搜索","authors":"Jheng-Jhe Sie, Shang-Chen Yang, Zih-Yun Hong, Chien-Kai Liu, Jen-Jee Chen, S. C. Li","doi":"10.1109/ICS.2016.0097","DOIUrl":null,"url":null,"abstract":"With the more and more serious population aging problem, the demand of long-term care is increasing. Actually, most of the aging people have the ability to take care of themselves, some warm concerns, medical advices, and timely remainders can effectively improve their living quality. Therefore, an automatic system to track and record elderly people's daily life and activities is required. In this paper, we propose a Long-term cArE-based Smart hOme platform (LAESO), which integrates the cloud, IoT, sensor networks, and community. The proposed LAESO platform combines with a variety of services, such as motion detection, activity detection and log, e-Care, indoor positioning, location-based real-time video monitoring, emergency notification, and lost elderly searching. Detected motions and activities of the elderly will be logged on to the cloud platform. With the log, e-Care can produce graphics and charts by doing statistics. Accordingly, family members and caregivers are able to understand the daily life and activity changes of the elderly. Moreover, we integrate the particle filter and 9-axis sensor to provide indoor positioning. LAESO platform also develops the emergency notification and location-based real-time video monitoring services to handle emergency events, i.e., the elderly falls down. Finally, we propose a novel lost elderly searching method, which combines the GPS positioning and crowd sensing to help find the missing elderly. Our real prototyping experience and some experimental results are also reported.","PeriodicalId":281088,"journal":{"name":"2016 International Computer Symposium (ICS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Integrating Cloud Computing, Internet-of-Things (IoT), and Community to Support Long-Term Care and Lost Elderly Searching\",\"authors\":\"Jheng-Jhe Sie, Shang-Chen Yang, Zih-Yun Hong, Chien-Kai Liu, Jen-Jee Chen, S. C. Li\",\"doi\":\"10.1109/ICS.2016.0097\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the more and more serious population aging problem, the demand of long-term care is increasing. Actually, most of the aging people have the ability to take care of themselves, some warm concerns, medical advices, and timely remainders can effectively improve their living quality. Therefore, an automatic system to track and record elderly people's daily life and activities is required. In this paper, we propose a Long-term cArE-based Smart hOme platform (LAESO), which integrates the cloud, IoT, sensor networks, and community. The proposed LAESO platform combines with a variety of services, such as motion detection, activity detection and log, e-Care, indoor positioning, location-based real-time video monitoring, emergency notification, and lost elderly searching. Detected motions and activities of the elderly will be logged on to the cloud platform. With the log, e-Care can produce graphics and charts by doing statistics. Accordingly, family members and caregivers are able to understand the daily life and activity changes of the elderly. Moreover, we integrate the particle filter and 9-axis sensor to provide indoor positioning. LAESO platform also develops the emergency notification and location-based real-time video monitoring services to handle emergency events, i.e., the elderly falls down. Finally, we propose a novel lost elderly searching method, which combines the GPS positioning and crowd sensing to help find the missing elderly. 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Integrating Cloud Computing, Internet-of-Things (IoT), and Community to Support Long-Term Care and Lost Elderly Searching
With the more and more serious population aging problem, the demand of long-term care is increasing. Actually, most of the aging people have the ability to take care of themselves, some warm concerns, medical advices, and timely remainders can effectively improve their living quality. Therefore, an automatic system to track and record elderly people's daily life and activities is required. In this paper, we propose a Long-term cArE-based Smart hOme platform (LAESO), which integrates the cloud, IoT, sensor networks, and community. The proposed LAESO platform combines with a variety of services, such as motion detection, activity detection and log, e-Care, indoor positioning, location-based real-time video monitoring, emergency notification, and lost elderly searching. Detected motions and activities of the elderly will be logged on to the cloud platform. With the log, e-Care can produce graphics and charts by doing statistics. Accordingly, family members and caregivers are able to understand the daily life and activity changes of the elderly. Moreover, we integrate the particle filter and 9-axis sensor to provide indoor positioning. LAESO platform also develops the emergency notification and location-based real-time video monitoring services to handle emergency events, i.e., the elderly falls down. Finally, we propose a novel lost elderly searching method, which combines the GPS positioning and crowd sensing to help find the missing elderly. Our real prototyping experience and some experimental results are also reported.