| Summary: | 碩士 === 國立臺南大學 === 電機工程學系碩博士班 === 104 === With the population aging problem is more serious, the long-term care needs are also increasing. Relatives and friends can’t take care of the elderly because people have many work need to do nowadays. Actually, most of the aging people (over 65) have the ability to take care of themselves, and some warm concerns, medical advices, and timely reminders can effectively improve their living quality, that not only set relatives and friends mind at rest but also maintain theirs relationship. Therefore, we need an automated system to help elderly tracking and record daily life that can help relatives or medical personnel find out the elderly’s health and take some warm concerns.
In recent years, the Internet of Things (IoT) is the one of the most popular topic, in which device can be connected with each other via networks. The devices become conscious and smart let our life more safe and convenient. Nowadays, people are dependent on the social network increasingly, so this thesis presents a long term care system which integrates cloud, Iot, and the social network to improve elderly people’s living convenience and mind health.
In this thesis, we build a long-term elderly care platform that combines with a lot of sensors, appliances, indoor localization tracking via Bluetooth, cloud, wearable devices, social network, mobile device application and a general idea of crowd sensing to provide a wide range of care services for the elderly, such as traceability and real-time location monitoring of real-time video monitoring system activity logs, e-Care service, fall detection and lost elderly searching service. Because relatives and friends can’t take care of the elderly all the time, we use Particle filter algorithm via Bluetooth device and 9-axis sensor to track indoor position that can build a real-time monitoring system with WebCam. Furthermore, this thesis not only set up activity detection log service but also use K-mean and K-nearest neighbor algorithm via acceleration sensor to determine what is the elderly doing now and build log. E-care service provides aggregated and analysis activity log functions and generating graphical interface and chart for relatives or medical care personnel to observe the elderly’s daily routine regular or not. Moreover, for emergencies, such as the elderly fall down, cloud platform will inform relatives via Google cloud messaging (GCM) service. Finally, we propose combine GPS positioning Records and social network searching solution via Bluetooth to solve the problem of the elderly lost. Our real prototyping experience and some experimental results are also reported.
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