APPLICATION OF AUTOMATED INTELLIGENT VIDEO SURVEILLANCE SYSTEM WITH DEEP LEARNING CAPABILITY FOR SAFETY MONITORING IN MANUFACTURING SECTOR

Abstract

In many cases, occupational and accidental injuries arise from the neglect of employees and the failure of upper management to ensure the constant adherence to safety regulations. Nevertheless, occupational accidents can also result from a combination of factors such as the presence of potential hazards in the workplace and unsafe actions or procedures. Traditionally, to mitigate safety risks in the workplace, security personnel are employed to carry out safety checks and monitoring, a process that can be arduous and inefficient, particularly in large spaces like factories. The objective of this article is to assess previous studies pertaining to the application of intelligent visual surveillance through deep learning methods in enforcing safety regulations. The paper also discusses the use of deep learning in safety management across various sectors. Notably, as far as our knowledge extends, there currently exists no comprehensive survey or initial assessment of deep learning for safety management specifically within manufacturing facilities. This survey is intended to serve as a catalyst for future research into the implementation of intelligent visual surveillance through deep learning for safety management and regulatory purposes.