Article Details

Abstract

With the rapid development of China's economy, the technology used in industrial parks has been continuously upgraded, and the scale of the park has been expanding. In the past, the use of manual safety management of the parks has gradually become weak, and it requires a lot of manpower, material resources and time. It is difficult to adapt to the management needs of modern parks. At present, there is a lack of effective management methods for people, vehicles and objects in industrial parks. The main safety hazards include stranger access, vehicle access and the occurrence of fires. In view of the above problems, this paper adopts a method based on Artificial Intelligence to realize the functions of personnel behavior training and detection, smoke and open fire detection, face-based identity authentication, vehicle access management and data centralized management in industrial parks. In this paper, PyTorch is used as the Artificial Intelligence computing framework, YOLOv7 algorithm is used to realize intelligent detection, and K3s container orchestration technology is used to realize the deployment of services. The system is simulated test to meet the safety management needs of industrial parks of different sizes.

Keywords

industrial park; safety management; Artificial Intelligence; YOLOv5; K3s

References

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Funding

Science and Technology Project of Jiangxi Provincial Department of Education (GJJ210817)

About the authors

Chai Zheng (1982-), male, Han ethnicity, from Shangyu, Zhejiang, lecturer, master's student, research direction: digital signal processing.