Fall Detection System for Elderly Wellness Using LSTM and SVM

The project goal is to develop a computer vision system for detecting falls in elderly individuals. The elderly frequently encounter the danger of falling, which can result in serious injuries and a deterioration in their overall health. To address this issue, a fall detection project has been developed specifically for elderly individuals. The project utilizes machine learning algorithms to identify the elderly fall, which can lead to severe injuries and a decline in their overall health. By analysing video footage, the system will utilize advanced algorithms to identify specific patterns and movements associated with falls. The system will instantly alert caregivers or medical personnel when a fall is detected, enabling them to provide immediate assistance. With this technology, senior citizens' safety and well-being could be substantially improved, their risk of injury could be decreased, and their overall care could be improved. We are using LSTM and SVM approach to enhance the accuracy of the fall detection system.