Design of early warning system of risk for the activities of bulk cargo port vehicles picking up goods and data visualization

As the assembly point and hub of land and water transportation, the port is an important channel for the circulation of goods. Cargo security has always been the focus of the port’s attention, but cargo theft and fraud have occurred from time to time. In order to prevent such incidents from happening, this paper adopts the B/S architecture and Bayes-based port dry bulk cargo extraction risk prediction model, and designs the port vehicle extraction cargo risk by analyzing the port vehicle extraction cargo business process and the visualization requirements of key data Early warning system. Through various visual interfaces, the system can better help business personnel intuitively judge whether there is a risk in the activities of vehicles picking up goods, so that real-time tracking and control measures can be taken to reduce the risk of goods theft, which is of practical significance to the development of the port.