Research on Detection Errors or Misidentifications Regarding Workers' Mobile Phone Usage Behaviors During Work

Huixin Liu

doi:10.62051/ijcsit.v7n1.04

Authors

Huixin Liu

DOI:

https://doi.org/10.62051/ijcsit.v7n1.04

Keywords:

Behavior detection, Behavior recognition

Abstract

In recent years, news about major accidents caused by workers using mobile phones while on the job has emerged frequently, drawing widespread attention from society. With the advancement of artificial intelligence, detection methods based on deep learning have gradually replaced manual supervision, becoming a current research hotspot. Although the technology for detecting mobile phone usage behavior is now relatively mature, it still has some flaws. For instance, mistakes or misidentifications in detecting workers' mobile phone usage behaviors still occur from time to time. This project aims to improve and refine the existing technology for detecting workers' mobile phone usage behavior, enhance detection accuracy and precision, reduce the misjudgment rate, and avoid related risks and losses caused by misjudgments. It will help enterprises accurately identify workers' mobile phone usage during work, thereby improving work efficiency and reducing safety hazards.

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