Design And Implementation Of Intelligent Construction Site Equipment Real-time Early Warning System Based On Stream Processing

The reform and innovation of information technology bring infinite possibilities and surprises to modern engineering construction management.If the construction industry wants to develop at a high speed,it is very important to combine it with information technology means such as Internet and artificial intelligence.However,in recent years construction site equipment safety accidents occur frequently,resulting in personal accidents and heavy losses of site property.In order to reduce the probability of equipment accidents,it is necessary to design a set of smart site safety supervision system for the construction site to monitor the site equipment and improve the safety of the construction site.The real-time operation data of the equipment is usually transmitted to the system in the form of flow,and the quality supervision personnel often pay more attention to the uprush of alarm during a certain time period.In view of this,this paper designs a set of construction site equipment early warning system based on flow processing technology.For the anomaly detection of the uprush of alarm volume of equipment during a certain time period,this paper uses the mutation point anomaly detection method to label the anomaly label of sudden increase in early warning volume,and then constructs an anomaly detection model based on Copula function to further detect anomalies.The experimental results show that the performance of the anomaly detection algorithm based on Copula function is better than other algorithms.The anomaly detection algorithm based on Copula function has the characteristics of low computational overhead,strong generalization ability,scalability and high interpretability.For the anomaly detection problem of the sudden increase of the total amount of early warning of equipment,this method has high practical application value.For the equipment operation flow data,this paper realizes the data exchange with the help of message middleware,adopts the complex event processing engine,and realizes the event filtering by relying on the anomaly detection model based on Copula function.Finally,the qualified events are notified to the relevant personnel and recorded.The scheme has been tested,and its real-time detection meets the needs of users,and has high application value.For the construction of early warning system,this paper comprehensively designs the system according to the life cycle of software engineering,adopts MVC architecture mode,front and rear end separation technology and data storage technology based on Web,and realizes the management of attendance equipment,construction equipment and environmental quality monitoring equipment and the statistical analysis function of early warning information.Based on wechat applet,the closed-loop measures from proposal to solution of early warning record are realized.The system has passed the function test and performance test.The results meet the needs of users and have high application value.