IMPLEMENTATION OF A SYSTEM FOR MONITORING THE WORK OF GROUND EQUIPMENT IN OPEN PITS OF GOLD MINING ENTERPRISES BASED ON COMPUTER VISION TOOLS
The main task of the proposed research is to organize automatic monitoring of equipment operation in an open pit of a gold mining enterprise. The solution to this problem made it possible to reduce the risk of errors in accounting for the volume of work performed by mining equipment. An additional result is an increase in the accuracy of planning the economic indicators of the firm. The problem is solved using a computer vision system built based on a B2710RVZ street surveillance camera and an artificial neural network of YOLO v3 architecture, operating based on a Jetson Nano single board computer. The neural network was trained on a personal computer with an Nvidia GeForce 1060 video card. The implemented system showed very high accuracy, correctly recognizing from 99 to 100% of technological loading operations. The result allows us to speak about the possibility of automating the accounting and control of the process of surface mining equipment using simple and relatively cheap means based on computer vision technologies.