Author(s)

Zhanliang Wang

Corresponding Author

Zhanliang Wang

ABSTRACT

As a significant part of the national economy of a country, the construction industry is closely related to people’s lives. In recent year, with the booming development of the construction industry, the rate of safety accidents on construction sites is also on the rise. The management of potential safety hazards in construction sites has attracted more and more attention of people. As a kind of personal head protection equipment, the helmet is required to be worn by every worker in construction sites. But for now, the wearing of workers' helmets mainly depends on manual supervision, which is very inefficient. With the development of economy and the progress of science and technology, Artificial Intelligence technology has been widely used, which can provide a certain technical support which is more efficient for the management of construction site safety issues. Thus, this article proposed a safety detection and early warning system for the supervision of the wearing of workers' helmet by using artificial intelligence technology. In my work, I will implement the YOLO algorithm which is a useful object detection algorithm to realize the processing and analysis of real-time surveillance video. And I will realize the linkage control of intelligent detection and early warning through the combination of real-time monitoring and the system, in order to improve the efficiency and accuracy of safety management on the construction sites and reduce the incidence of safety accidents.

KEYWORDS

Artificial Intelligence, Safety management, Construction industry, Helmets wearing detection