A Machine Learning based Activity Recognition for Ambient Assisted Living
U Chandini · International Journal on Future Revolution in Computer Science & Communication Engineering · 2018
Ambient assisted living (AAL) technology is of considerable interest in supporting the independence and quality of life of older adults. As such, it is a core focus of the emerging field of gerontechnology, which considers how technological innovation can aid health and well-being in older age. Human activity recognition plays a vital role in AAL. Successful identification of human activity is crucial for any assistive care services for elderly people living alone in a home. In this paper, a method for activity recognition is proposed which recognizes or classifies activities based on sensor data. The method uses most trending algorithm in deep learning domain, i.e. LSTM to build the model .The proposed method is evaluated using a well known activity sensor dataset.