Qualitative analysis of techniques for device-free human activity recognition

Abstract

Continuous human monitoring has become increasingly important in various applications, including health, security, intelligent systems, and leisure activities. Human Activity Recognition (HAR) through the use of wearables, tagged objects, and device-free localization (DFL) has gained major attention from researchers. DFL approaches have been particularly recommended due to their non-intrusive nature and its applicability in diverse fields. The use of Artificial Intelligence (AI) has reinvented the utilization of deep concealed information for precise detection and interpretation. However, challenges which includes data collection, dealing with intra-class variability, and real-Time recognition in dynamic and instant changing scenarios still persists. This paper provides a review of the various techniques for HAR and their applications in different fields. A comprehensive analysis of methodologies and data from papers published from 2000 to 2023 has been conducted. The paper also discusses research problems and future opportunities in this field.