Design of optimal deep learning based human activity recognition on sensor enabled internet of things environment

Abstract

Human activity recognition has become an important area in smart healthcare and Internet of Things environments. This study designs an optimal deep learning based human activity recognition model for sensor-enabled IoT environments. The model involves preprocessing, feature extraction, and classification using deep learning, with parameter optimization to improve recognition performance on sensor activity data.