Automatic Fall Detection And Alert System For Home Safety
Abstract
Falls are a regular issue for the elderly and the disabled, and they can result in serious injuries or even death. We have created fall detection systems that use image processing methods to quickly identify falls in order to solve this problem. The device employs a camera to take pictures or videos of the person it is watching, then analyses the images to determine whether a fall has occurred. The photos are analyzed to see if a fall has occurred using image processing techniques like object recognition, motion analysis, and background subtraction. To ensure quick assistance, the system then notifies a carer or emergency contact. The use of image processing in a fall detection system offers a potentially effective way to address the issue of falls among the elderly and disabled. It offers an efficient, trustworthy, and affordable substitute for conventional fall detection techniques and can significantly increase the safety and well-being of people who need it most.
Keywords:
K Nearest Neighbor, MVC, Gaussian mixture model (GMM), Fall motion mixture model (FMMM)
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