Automatic Alert and Triggering System to Detect Persons’ Fall Off the Wheelchair

Abstract

Sensor-based human activities need a lot of attention in the driving technologies of the Internet of Things (IoT) because it should set the human activities (make and perform personal assisting tasks) that should be performed well. Taking care of physically disabled persons and preventing them from falling from a wheelchair are vital tasks to be performed. Scrutinizing these kinds of accidents via surveillance systems based on CCTV cameras would not prevent them from falling from the wheelchair. In the present work, a solution to detect and signal the situation, an intelligent and cost-effective fall detection system is presented. This module utilizes the benefits of the advanced technology, i.e., the Internet of Things (IoT). Here, an ultrasonic sensor is fixed on to the wheelchair to detect the obstacles such as pits, stairs, and an accelerometer to detect human movements. These sensors are connected through a microcontroller to transmit acceleration data continuously. The system monitors the falls and abrupt changes in the person's movement. A sudden jerky change in the system is treated as a crash or fall. The system senses these changes and automatically triggers a warning via the Wi-Fi connection and sends information to the near ones about the situation via the Blynk application.