Research on the Development of On-Site Human Activity Recognition and Supervision Tools Based on Fuzzy Algorithms

This article is aimed at the limitations of human judgment in on-site supervision work for human behavior. It proposes a human activity recognition method based on fuzzy algorithms and develops a corresponding on-site supervision tool. Firstly, a comprehensive fuzzy evaluation model is established to fuzzify and accurately recognize human behavior. Subsequently, considering the on-site conditions and requirements, a portable on-site tool integrated with fuzzy algorithms is developed. This tool can monitor and identify human behavior in real-time, as well as provide auxiliary decision-making and data transmission functions, effectively improving the efficiency and accuracy of on-site supervision work. Finally, experimental results demonstrate that this method and tool exhibit high accuracy and practicality, and can be widely applied in various fields.