Fall Detection & Daily Living Activity Recognition using CNN

Understanding human behaviour and incorporating users' social circumstances into computer systems are the two main objectives of the emerging academic field known as “human-centered computing”. One of the more cutting-edge, challenging, and alluring applications of the framework is the sensing of human body mobility utilizing mobile devices to gather context information on people's actions. This study suggested a deep learning-based automated fall detection solution. A collection of carefully chosen characteristics acquired by tracking human body silhouettes are input into a CNN -based classifier.