Research on Safety Management and Control of Oil Depots Based on Computer Vision

In view of the limitations of traditional safety management and control modes in oil depots, such as manual inspections, video surveillance, and automatic alarms, this paper, based on computer vision technology, focuses on designing the framework of an intelligent video analysis platform for oil depot safety management and control. It analyzes the impacts of factors like light changes and small targets in the complex environment of oil depots on target detection, along with corresponding solutions. Additionally, it conducts a comparative analysis of the advantages and disadvantages of three methods for identifying static protective clothing in oil depots. Moreover, a safety helmet detection model for oil depots based on YOLO8 has been constructed. The research findings are bound to support the construction of smart oil depots, promote the actual implementation of the three - tier intelligent safety management and control platform consisting of the general oil company, provincial oil companies, and oil depots, and ensure the intrinsic safety of oil depots.