Human Activity Detection Using Deep Learning and Bracelet with Bluetooth Transmitter

The use of artificial intelligence, machine learning, and deep learning is finding its purpose in various fields nowadays. This paper describes a study in which Internet of Things and deep learning are used to implement human activity detection based on data collected from bracelet equipped with Bluetooth transmitter. The main focus of the study was development of a prediction model using deep learning that would help elderly people and their caretakers. Time series data about elderly people activity was collected from bracelet using a Bluetooth gateway and IoT platform, and later annotated based on the activity logs they kept in a form of diary. A neural network is trained to classify data into two groups (binary classification problem) corresponding to activity of the person wearing the bracelet. Initial study shows promising results of the presented approach for the use in human activity detection for elderly.