Mapúa Institute of Technology at Laguna
SSIP 2020: 2020 3rd International Conference on Sensors, Signal and Image Processing October 2020, Pages 31–40
ACM International Conference Proceeding Series (ICPS)
Publication Date: 3-28-2021 https://doi.org/10.1145/3441233.3441245
Fall Detection, Location and Identification for Elderly Institution
Authors: Kristine Joyce Ponce Ortiz, and Allerick Insorio Martin
Malayan Colleges Laguna
Abstract – This paper focused on the development of a system that could detect and locate falls, and identify the victims in a short period of time. The system used triaxial-accelerometer in detecting a fall, signal strengths from access points in locating the position, and media access control (MAC) addresses in identifying the name of the victim. Wemos D1 was used as the microcontroller in measuring and averaging signal strengths, computing the resultant acceleration coming from the MPU6050 triaxial-accelerometer and sending the values together with the MAC address to the database. The software developed accesses the database, computes for the location, and displays the outputs to the user while sounding an alarm. To test its functionality, different categories of testing were conducted. The fall function was tested and produced a recall of 100% and a precision of 97.5%. The response time was measured by how much time it took from the event of the fall to the software displaying the location and sounding the alarm. The computed average response time was 1.1128 seconds and was considered low and fast enough. The displaying of the location was tested while considering the size of the area of the testing. The area considered had the size of 10 m by 6 m and the test produced accuracies of 82.8% and 90% on x and y axes respectively. This means that the margin of error for the x-axis was 1.72 m and 0.6 m on the y-axis. In the end, the fall detection system was able to perform its function and provide reliable output that could help elderly institution, as well as elderly people, to lessen the risks and consequences of a fall.
Keywords – triaxial-accelerometer, access points, media access control (MAC), database
Citation – Kristine Joyce Ponce Ortiz and Allerick Insorio Martin. 2020. Fall Detection, Location and Identification for Elderly Institution. In 2020 3rd International Conference on Sensors, Signal and Image Processing (SSIP 2020). Association for Computing Machinery, New York, NY, USA, 31–40.