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An Intelligent Wearable and Mobile System for the Automated Falling Detection and Protection using Machine Learning and Internet-Of-Things

Authors

Zimi Zeng1, Ziyu Huang1 and Jonathan Sahagun2, 1USA, 2California State Polytechnic University, USA

Abstract

In today's society, elderly adults living alone face various challenges. From this we can feel the indifference of modern society and the danger of falling for elderly people living alone. By recounting my grandfather's personal experience of a fall, the urgent need for assistance among elderly adults and the potential dangers of isolation are highlighted. The core question is: How can technology be used to improve the safety and overall quality of life of elderly adults living alone [1]? To solve this serious problem, we developed a fall detection device. When elderly adults wear fall detection devices, it can address these challenges by providing a mechanism to send instant alerts to family members through a connected app in the event of a fall or emergency. The device aims to improve the safety and well-being of the elderly, provide timely intervention, reduce social burdens, and solve potential social problems [2]. In addition to direct benefits, fall detectors have significant commercial value and can have a positive impact on the quality of life of older adults. The device enhances physical and mental health, increasing independence and safety in outdoor activities with fall detection and emergency alert features [3]. Fall detectors not only have commercial value, positive impact and wider social contribution, they can also play a role in addressing social neglect and inspiring elderly adults to make positive changes.

Keywords

Internet-Of-Things, Machine Learning, Mobile System