With the rapid development of deep learning technology, more and more intelligent algorithms have been applied. The hardware equipment used for training and calculation is mainly GPU, which will incur high hardware procurement cost and power consumption cost in the actual deployment and use. Therefore, aiming at the high cost of the current deep learning system, this study proposes to use raspberry PI and Movidius neuron computing stick as the computing platform. SSD+MobileNet algorithm is adopted to realize the recognition and detection of vehicle targets, and the training model is tested and optimized in the actual environment to finally meet the effect of actual use, with a processing speed of 4 frames per second on average. The experimental results show that on the platform with weak computing power like raspberry PI, the algorithm can be accelerated by VPU modules like Movidius neuron computing stick, and the computing cost can be greatly reduced when it is in actual use.