Authors: Carlos Antonio Guanzon, Briane Paul V. Samson
Pages: 1–11
Falls remain a prevalent issue in the healthcare industry. Hundreds of thousands of unintentional deaths happen yearly because of falls. This is especially true with the elders, as they are the most prone to falls. To solve this, fall-detection systems have been developed to detect when a person has fallen. Generally, fall-detection systems are capable of detecting when a person has fallen and landed on the floor, but there has been a lack of research on preventing falls altogether. This study aims to solve this by developing the first fall-prevention system. This system will be built on a Jetson Orin NX 8 GB board with 3 RGB cameras for object detection and a ToF camera for depth measurement. This study introduces a novel fall-prevention system that is capable of preventing falls that happen from tripping entirely, which, in turn, will lessen the amount of unintentional deaths that happen yearly.
Proceedings of CHIRP 2025, May 8 2025, Baguio, Benguet