Intelligent construction site vehicle congestion monitoring system based on block chain

Abstract

The invention discloses an intelligent construction site vehicle congestion monitoring system based on a block chain, whrein the system comprises a terminal cluster and a computing cluster, the computing cluster loads parameters required for building an intelligent construction site vehicle thermodynamic diagram prediction deep neural network and parameters required by a vehicle congestion judgment unit, an intelligent construction site vehicle congestion monitoring block chain private chain is configured, intelligent construction site vehicle congestion monitoring reasoning is executed, and intelligent construction site vehicle congestion monitoring is achieved, wherein the input of the intelligent construction site vehicle congestion monitoring deep neural network is a monitoring area vehicle image acquired by a terminal, and the output comprises a vehicle wheel thermodynamic diagram; and the vehicle congestion judgment unit is used for analyzing the vehicle wheel thermodynamic diagram in the sliding time window and judging whether vehicle congestion exists in the construction site or not. According to the invention, in construction site environment monitoring, the construction site vehicle jam monitoring precision, the monitoring efficiency and the safety and confidentiality in the data processing and transmission process are improved.

Description

technical field [0001] The invention relates to the technical fields of artificial intelligence, block chain, CIM, and smart construction site, and in particular to a block chain-based smart construction site vehicle congestion monitoring system. Background technique [0002] With the development of my country's economy and the advancement of urbanization, more and more urban construction projects have spawned more and more construction sites, that is, construction sites. In urban construction projects, efficiency is a very important indicator. The scheduling efficiency of building materials transportation also directly affects the construction efficiency of the construction site. On the one hand, high construction efficiency requires more trucks to transport building materials. On the other hand, more trucks are likely to cause vehicle congestion on the construction site, greatly delaying the progress of construction operations and reducing construction efficiency. Moreov...

AI Technical Summary

Problems solved by technology

[0003] The traditional method of detecting vehicle congestion uses feature extraction, and calculates the queue length according to the feature points, and judges through the relationship between vehicle speed, queue length and the set threshold. This type of method is not real-time, and the calculation is too complicated, which affects the accuracy of parameters High requirements, poor application prospects

Moreover, the current monitoring of site conditions usually only returns abnormal results, and the result feedback is single

In addition, the cluster used for computing, information is easy to be leaked, and the security performance is low

Therefore, the existing construction site vehicle congestion monitoring technology has the problems of poor real-time monitoring and low monitoring efficiency, single result feedback, and low safety performance in the process of data processing and transmission.

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