Automatic Fall Detection System of Unsupervised Elderly People Using Smartphone

With the increasing elderly population around us, complications in ensuring their proper welfare are also on a rise. Among these, unsupervised falling or collapsing is one of the main problems we face regarding elderly people. Though the prevention of fall should unarguably be the main focus but practically that can never be achieved with a full guarantee. Hence, development of systems that can detect unsupervised fall and inform concerned group(s) immediately is a necessity. This paper aims at building a system that will automatically detect the fall of an elderly person and immediately inform those in charge of his/her well-being. Although visual sensors offer an easy way to do that, considering the cost, inconvenience, and privacy, this research is based on building a system using motion sensors. The objective is to build the system with an existing device so that it would not be necessary to buy a new device to use this system. Keeping this in mind, we used smartphones as the main component of our system as it is widely used by almost everyone. We want to achieve convenience, accuracy and cost effectiveness for our system to be successful. A dataset was first established and by analyzing it, an appropriate algorithm was devised. Finally, the algorithm was implemented and the system was tested and fall was detected in real time.