整合云计算、物联网和社区,支持长期护理和失散老人搜索

Jheng-Jhe Sie, Shang-Chen Yang, Zih-Yun Hong, Chien-Kai Liu, Jen-Jee Chen, S. C. Li
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引用次数: 7

摘要

随着人口老龄化问题的日益严重,对长期护理的需求日益增加。事实上,大多数老年人都有照顾自己的能力,一些温暖的关怀,医疗建议,及时的关怀可以有效地提高他们的生活质量。因此,需要一个自动化系统来跟踪和记录老年人的日常生活和活动。在本文中,我们提出了一个基于长期护理的智能家居平台(LAESO),它集成了云、物联网、传感器网络和社区。提出的LAESO平台结合了多种服务,如运动检测、活动检测和日志、e-Care、室内定位、基于位置的实时视频监控、紧急通知和走失老人搜索。检测到的老年人的动作和活动将被登录到云平台上。有了日志,e-Care可以通过统计生成图形和图表。因此,家庭成员和照顾者能够了解老年人的日常生活和活动变化。此外,我们还集成了粒子滤波器和9轴传感器来提供室内定位。LAESO平台还开发了紧急通知和基于位置的实时视频监控服务,以处理突发事件,如老人摔倒。最后,我们提出了一种将GPS定位与人群感知相结合的寻失老人新方法。本文还报道了我们的实际样机制作经验和一些实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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