A Survey on Truth Discovery in Crowdsensing - Peng, Yadong; Wang, Tianxi; Lang, Qing (Computers and Artificial Intelligence, 2025)
In recent years, the rapid proliferation of smartphones and wearable devices has significantly propelled the development of crowdsensing. As a prerequisite for ensuring the secure operation of crowdsensing services, data quality has emerged as a critical issue that demands urgent resolution. This paper first introduces the main components and system workflows of crowdsensing, followed by an account of the basic concepts, principles, and key research focuses of truth discovery methods in crowdsensing. By categorizing truth discovery approaches based on modeling paradigms, this study systematically reviews the current research landscape, analyzes and compares existing methods, and constructs a comprehensive framework for their evaluation. Finally, it synthesizes the findings and identifies future challenges for truth discovery in crowdsensing, aligning with the evolving application demands of the field.