(SCC 2021) Design of IoT Health Pension Scheme based on Physiological and Behavioral Indicators for Elderly

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Abstract: In recent years, the health and safety problems of the elderly increase contin-uously, coupled with the age of information technology, the elderly are diffi-cult to adapt to the society, so the use of modern Internet technology to pro-tect the health and personal safety of the elderly, has become a top priority. Therefore, this paper, based on the Internet of Things technology, mainly monitors the elderly's indoor behavior, supplemented by the monitoring of physiological indicators, outdoor behavioral trajectories and falls, proposes the Internet of Things health pension scheme design based on the physiologi-cal and behavioral indicators of the elderly. This scheme involved the mini-mum confidence interval solution strategy, according to the old people in dif-ferent parts of the activity rate for the elderly indoor dwell time detection, and combined with travel anomaly detection algorithm, pulse wave signal analy-sis algorithm, fall detection algorithm and other algorithms, real-time moni-toring of physiological indexes of elders trajectory data and behavior, the guardian and the hospital can check at any time, once the old man has an ac-cident. The system will send abnormal information to the monitoring system of WeChat mini program guardian and community hospital in time, and the corresponding personnel will immediately take treatment measures to ensure the health and safety of the elderly. This system combines the health and safety problems of the elderly to consider the possible accidents, from moni-toring, prevention and treatment, the elderly, children and the hospital are closely linked together, to ensure the health and safety of the elderly to pro-vide a comprehensive solution.

Authors: Quan Yuan (Wuhan Collage 52420000757037833G, China); Mao Li (WuHan College, China); Xiaohu Fan (Wuhan Collage & Wuhan Optic Valley Info&Tech Co., Ltd., China); Rui Zhou and Hu Su (China); Hao Feng, Jing Wang and Siyao Wang (Wuhan College, China)

Email: 2432986062@qq.com, 646875396@qq.com, fanxiaohu@foxmail.com, 154040067@qq.com11109797@qq.com3395214965@qq.com

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