Ali Kohan - Department of Computer Engineering, Fasa University, Fasa, Iran.

Human Activity Recognition (HAR) is a field of study within artificial intelligence and computing that focuses on developing systems capable of identifying and categorizing human activities based on data from various sensors. This field involves the identification and categorization of human activities using different sensor technologies. This paper thoroughly explores some latest methods and progress in recognizing human activities. Subsequently, we discuss important advancements in sensor technology, feature extraction, machine learning algorithms, and incorporating deep learning approaches. The goal of this review is to provide a clear resource for researchers, practitioners, and enthusiasts, helping them understand the landscape of human activity recognition and guiding future research in this dynamic field.

Human activity recognition, Convolutional neural networks, Deep learning, Genetic algorithm