Fall Detection Using Object Detection

Author(s)	Prini Rastogi, Shruti Sharma, Srujan Marri, Ali Mulla
Country	India
Abstract	The growing number of elderly citizens has raised critical issues about the safety of the elderly, specifically about falls that frequently result in serious injury. This paper reports the design and development of a fall detection system using object detection methods. The system is based on the application of machine learning and computer vision methods to recognize and analyse human body motion in real-time to detect abnormal patterns of motion typical of falls. The system applies a pre-trained object detection model to process video frames efficiently to detect human bodies and monitor their movement, classifying between normal movement and falls. When a fall is detected, an alert is sent to the local host by an alert notification. The proposed system is designed to offer a low-cost, non-invasive fall detection system with potential applications for nursing homes and healthcare. The experiments show that the system is effective in properly detecting falls and low in false positives, offering a safe and reliable method for ensuring the safety and well-being of the elderly.
Keywords	Fall Detection, Object Detection, Computer Vision, Machine Learning
Field	Computer Applications
Published In	Volume 6, Issue 5, May 2025
Published On	2025-05-03
Cite This	Fall Detection Using Object Detection - Prini Rastogi, Shruti Sharma, Srujan Marri, Ali Mulla - IJLRP Volume 6, Issue 5, May 2025.

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