摘要：

With the development of industry and society, explosives are widely used in social production as an important industrial product and require transportation. Explosives transport vehicles are susceptible to various objective factors during driving, increasing the risk of transportation. At present, new transport vehicles are generally equipped with intelligent driving monitoring systems. However, for old transport vehicles, the cost of installing such systems is relatively high. To enhance the safety of older explosives transport vehicles, this study proposes a cost-effective intelligent monitoring system using consumer-grade IP cameras and edge computing. The system integrates YOLOv8 for real-time vehicle detection and a novel hybrid ranging strategy combining monocular (fast) and binocular (accurate) techniques to measure distances, ensuring rapid warnings and precise proximity monitoring. An optimized stereo matching workflow reduces processing latency by 23.5%, enabling real-time performance on low-cost devices. Experimental results confirm that the system meets safety requirements, offering a practical, application-specific solution for improving driving safety in resource-limited explosive transport environments.

DOI：10.3390/app15074072