People above the age of 65 are now more susceptible to a variety of ailments. It’s the age when people relax and stay at home while their family members are at work. Passing out unconscious is one of the most prevalent signs of a number of health conditions. One of the most common difficulties that elderly people encounter is the chance of falling by slippery surfaces or any obstacle. Falls are one of the leading cause of death among the elderly if proper care is not provided in right time in all countries. This paper presents a fall detection system that monitors an elder person in real-time using Computer Vision and Machine Learning techniques. We are designing a system that will detect fall actions of the person and alert other people who can help or send help to the person whose fall action is detected. Data is collected live by making sample videos of different kinds of fall actions.
₹10000 (INR)
NON IEEE -2022