Application of Fall Detection for the Elderly: A Case Study of Thailand

Abstract

Nowadays, Thailand is ranked the third most rapidly aging population in the world. The number of people aged 60 and over stands at about 13 million or accounting for 20% of the population. By 2050, Thailand’s aging population is expected to increase to 20 million, accounting for 36% of the population. Most of elderly people who are too old to work, will be live alone since most of working people have to work and have not time to take care of them. When an accident occurs, and no one know, it is very serious. An important one of the most accidents is falling. If we can suddenly know that the elderly’s fall and hurry to rescue, it will increase the elderly’s chance to survive. Therefore, we implemented the fall detection system. Our research consists of three main parts: fall detecting, communication, and application. We developed a locket with a microcontroller, accelerometer, GPS (Global Positioning System), and communication module inside. When the sensors detect fall, this system is activated. An application will display the notifications (elder identification number, map of location, and the elderly’s profile) to users such as village health volunteer, hospital, or/and family members. We developed front-end of the application with Flutter framework and back-end with Loopback as a server framework. Computer programming is Node JS. Moreover, we used Firebase Cloud Messaging, and Google Map API. Consequently, we get this valuable innovation. Hopefully, it can help to reduce the mortality rate of the elderly fall. Also, it can reduce the family burden and government cost in taking care of them.