WHEELCHAIR-PERSON FALL DETECTION WITH INTERNET OF THINGS

Authors

  • Foong Seew Hon , Raed Abdulla , Sathish Kumar Selvaperumal , Chandrasekharan Nataraj , Dhakshyani Ratnadurai

Abstract

Falling down is among the major causes of medical problem that are faced by the elderly people
and movement disability person. These people tend to injure themselves from falling down when they alone.
When a falling event occurred, medical attention needs to provide immediately in order to reduce the risk of
faller from getting severe injuries which may lead to death. Several technologies have been developed which
some utilized webcams to monitor their activities. However, the cost of operation and installation is
expensive and only applicable for indoor environment. Some user also worried about their privacy issues.
Current commercialized device is by wearing a wearable wireless emergency transmitter which restrict
movement of user and produce high false alarm. This research proposed a wheelchair-person fall detection
system with IoT which is cost effective and reliable to detect fall and alert surrounding to call for help. For
fall detection, gyroscope, GPS module, FSR pressure sensor and microcontroller are implemented into the
system. The gyroscope is use to detect the position of the wheelchair while the FSR pressure sensor which
placed on the sit pad of the wheelchair will be used to detect and recognized the gesture of the user. Both
works together to detect fall event which increase the accuracy of the fall detection. GPS module used to
allocate the location of the wheelchair when fall event occur. When fall event occur, all the data includes the
location of the wheelchair will be sent to blynk mobile application. The IoT system will sent email
notification to the registered person to alert them fall event happen and help needed. Moreover, this system
requires less implementation cost and provides a quick response. It can install in the existing commercial
wheelchair. However, the limitation of this system is it required a good WIFI connection. For future
recommendation, a better GUI design can be implemented into the system besides that, more detection
system can be added on to increase the accuracy of the system

Published

2020-01-31

Issue

Section

Articles