Researchers from the UDG / NCC Monteengro will be presenting the paper titled “Human Activity Detection Using Deep Learning and Bracelet with Bluetooth Transmitter”, authored by S. Cakic, S. Sandi, D. Nedic, S. Krco and T. Popovic, at the upcoming IEEE TELFOR 2021 conference. The conference will be taking place on 23-24 November 2022. The paper presents the use of AI/ML algorithms to implement human activity detection based on data collected from wearable IoT device and the research is done through collaboration with DNET Labs, an innovation technology company from Novi Sad, Serbia. More info on the conference is available at the following link.
ABSTRACT – 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.
