Vehicle illegal behavior detection system based on block chain and deep learning

Abstract

The invention discloses a vehicle illegal behavior detection system based on a block chain and deep learning. The system comprises a shared feature extraction unit, a vehicle line pressing judgment unit, a safety belt wearing judgment unit and a license plate recognition unit, and all nodes in a cloud server cluster load parameters and weights required by a vehicle illegal behavior detection deepneural network. For each neural network reasoning request, a plurality of available nodes are selected from the cloud server cluster, the parameters of the network modules distributed in different available nodes are taken as block data, a block chain private chain is generated, and vehicle illegal behavior detection deep neural network reasoning is executed to realize vehicle illegal detection. In vehicle violation detection, safety belt wearing detection and line pressing detection are realized, and the detection precision and safety performance of the system are improved.

Description

technical field [0001] The invention belongs to the technical fields of deep learning and block chain, and in particular relates to a vehicle illegal behavior detection system based on block chain and deep learning. Background technique [0002] With the improvement of social and economic level and the increasingly developed transportation network, the number of urban car ownership has also increased on a large scale. Although there are traffic laws and regulations restricting the driving behavior of drivers, automobile violations that affect road traffic safety are still common in urban road traffic, such as illegal lane changes with solid lines and drivers not wearing seat belts. [0003] Cars illegally changing lanes and not following lane lines are important causes of local traffic congestion. The detection of these two illegal behaviors is based on vehicle line detection. And the driver does not fasten the seat belt and drives on the road for the sake of temporary ease...

AI Technical Summary

Problems solved by technology

The induction coil is easily damaged, the maintenance cost is high, the installation process is cumbersome and time-consuming, and the detection accuracy is low

There is still a lack of corresponding detection methods for whether seat belts are worn

Moreover, the server clusters used for computing are easy to leak information and have low security performance

[0005] Therefore, there are problems such as low detection accuracy, lack of seat belt wearing detection, and low system safety performance in the existing field of vehicle illegal behavior detection.

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