The Design And Implementation Of Construction Safety Digital Management And Control Platform

Since the reform and opening up,China’s construction industry has developed rapidly,its proportion in the national economy has been increasing,and its role in promoting the development of the national economy has become more and more obvious.However,the construction industry is also an industry with high risk and frequent safety accidents.Frequent safety accidents not only threaten the life safety of construction workers,but also seriously hinder the healthy development of the construction industry.In the traditional construction safety management mode,many works have to be completed manually,such as personnel statistics and equipment management.There are many problems such as low efficiency,error prone,high cost.In the face of the increasingly complex and changeable construction site,the traditional management mode has become more and more willing but insufficient,which is difficult to meet the management requirements of the new era.Therefore,it is imperative to improve the management level of construction site.In this regard,this thesis guides the safety management of the construction site according to the construction safety LCB theory,and uses the deep learning technology to intelligently monitor the dangerous behavior of on-site workers who do not wear safety helmets.Finally,a construction safety digital control platform is designed and implemented,which can help the construction manager manage the construction site from many aspects and improve the management level.The main work of this thesis is as follows:(1)This thesis investigates and analyzes some problems existing in the management of the construction site at present.At the same time,combined with the construction safety LCB theory,the requirements analysis of the platform is completed,and the requirements document is formed.After that,this thesis determines the overall architecture and functional architecture of the platform,then completes the database design of the platform,and finally carries out the detailed design.The front-end technology of the platform mainly includes the basic frameworks such as Vue.js and JeecgBoot,as well as the visual component libraries such as ECharts and Ant-Design-Vue,back end technologies mainly include SpringBoot and MySQL.After the overall development is completed,this thesis conducts necessary tests on each functional module of the platform to ensure that the platform can work normally.(2)In the construction safety management module,in addition to the remote real-time monitoring by using the monitoring camera arranged on the construction site,this thesis also utilizes the rapid development of deep learning technology in recent years to detect the dangerous behavior of not wearing safety helmets.At present,in the field of object detection,the YOLO series models have outstanding performance in terms of detection speed and detection accuracy,so this thesis selects YOLOv3 and YOLOv4 as candidate models,experiments are carried out on the company’s private FYD dataset and public datasets SHWD and HHWD,and multiple models are obtained.Among them,YOLOv4 model pre-trained with SHWD achieves the best performance on the target dataset FYD.Therefore,this thesis finally takes this model as the algorithm of safety helmet detection.The construction safety digital management and control platform designed and implemented in this thesis takes the construction safety LCB theory as the theoretical guidance of the safety management of the construction site,uses the deep learning technology to intelligently monitor the dangerous behavior without safety helmets on site,and realizes the digital and intelligent management of the construction site.The final completed platform meets the requirements for construction safety management in the new era,effectively guarantees the life safety of construction workers,effectively curbs the occurrence of safety accidents,and promotes the healthy development of the construction industry.