Research On Truck Dispatch System Of Open Pit Mine Based On Internet Of Things

The production of open pit mines requires the coordination of multiple departments, among which ore transportation is the most important production chain. With the advance of mining process, the distance and time of transportation increased, and the transportation cost increased accordingly. At the same time, in the truck production scheduling, there are conditions of unreasonable transportation program planning, large workload, and late traffic line adjustment, which restricts the increase of production efficiency. Under the severe economic situation of mining enterprises, using the Internet of things technology and wireless communication technology to build truck dispatching system furthest increase the unit capacity and reduced the production costs by the scheduling algorithm model, which is the effective way to improve the economic benefits of mining enterprises.In this paper, by deep understanding the production process of the production environment of open pit mine, according to the actual production needs of enterprises, using 4G mobile terminal and RFID tags, build a truck dispatching system. Using broadband wireless communication technology and TCP as the transmission and link mode, design the relevant scheduling model algorithm as the basis for scheduling. The efficient and reliable method of scheduling is realized by using the functions of the various parts.Firstly optimize road network model by graph theory and analyze the influence factors of the truck scheduling. Then, analyze the relationship among the factors and establish the traffic planning model with the appropriate scheduling algorithm under the consideration of multi objective optimization to gradually realize the static and dynamic scheduling. Finally, use Visual Studio 2012 and SQL Server 2008 to implement the scheduling model, build the truck dispatching system and deploy the system to the production enterprise. After using the contrast test, the system has achieved the expected effect, and can provide the decision support for the enterprise.