Abstract
Falls are the main cause of injury in the elderly people. Therefore, fall detection system in the elderly is an essential technology for aging society. This project was designed to develop the fall detection system based on wearable sensors and Internet of Things for the real-time fall detection, data storage, calculation, and notification. The raw data, kinematics signal from the daily living of elder, including three-dimensional accelerometer and gyroscope are provided by GY-85, which have been sent bidots cloud via NodeMCU-ESP32. Further, the NodeMCU-ESP32 avail of the raw data to specify the fall detection algorithm. Moreover, the NodeMCU-ESP32 is designed to achieve the seamless communication between the fall detection device and system to acquire and process the data anywhere anytime as long as there is wifi connection. Consequently, the Ubidots cloud is designed to perform the calculation based on support vector machine (SVM) theory. It also sends the fall detection result via LINE notification (chat application) to caregivers. The tests of the proposed system are performed based on activities of daily living and the directions that fall can occur. The results of the testing show that the proposed system can provide high accuracy and reliability in fall detection.
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