Design and Optimization of Lightweight Vehicle Real-Time Detection System Based on Edge Computing and Model Compression

Based on edge computing and model compression technology, this study designs and optimizes a lightweight vehicle real-time detection system. By introducing technologies such as pruning and quantization, the system reduces the computational complexity and memory usage to a certain extent, and the latency and memory consumption are appropriately reduced, while maintaining a reasonable detection accuracy to a certain extent. The system shows relatively stable performance in various scenarios such as daytime, nighttime, rainy days and foggy days, and the frame rate and power consumption are also moderately optimized. The optimized design alleviates the performance bottleneck of traditional vehicle detection systems on edge devices to a certain extent, and provides a more effective solution for intelligent transportation and autonomous driving applications.