Channel blockage detection method combining block chain and deep learning

Abstract

The invention discloses a channel blockage detection method combining a block chain and deep learning. The method comprises the following steps: constructing a channel blockage detection deep neural network, enabling the input of the network to be a collected monitoring region image, and enabling the output result of the network to be a detection result of whether a channel is blocked or not; andloading parameters required by the trained channel blockage detection deep neural network on a server cluster, configuring a channel blockage detection deep neural network reasoning block chain private chain for a channel blockage detection deep neural network reasoning request, and executing channel blockage detection deep neural network reasoning. In construction site channel blocking conditionmonitoring, channel blocking detection precision and detection efficiency are improved, and safety and confidentiality in a data processing and transmission process are improved.

Description

technical field [0001] The invention relates to the technical fields of artificial intelligence, block chain and CIM, in particular to a channel blocking detection method combining block chain and deep learning. Background technique [0002] With the rapid development of my country's social economy and science and technology, the traditional detection and management methods based on human resources in the construction site have many limitations, such as the high cost of pedestrian detection and management, and the low efficiency of detection and management. , The accuracy of detection is not high, it is easily affected by subjective factors, and the lack of human resources leads to problems such as ineffective management. There are problems in the construction site, such as the passage in the construction site being blocked by construction materials or machinery and equipment, which will affect the construction efficiency or hinder the normal passage of pedestrians. However, ...

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Problems solved by technology

[0002] With the rapid development of my country's social economy and science and technology, the traditional detection and management methods based on human resources in the construction site have many limitations, such as the high cost of pedestrian detection and management, and the low efficiency of detection and management. , the accuracy of detection is not high, it is easily affected by subjective factors, and the lack of human resources leads to problems such as poor management

There are problems in the construction site, such as the passage in the construction site being blocked by construction materials or machinery and equipment, which will affect the construction efficiency or hinder the normal passage of pedestrians. However, the cost of real-time supervision by manpower is too high and the efficiency is low. Supervise the influence of subjective factors of pedestrians and objective factors such as environment and line of sight occlusion

Moreover, the current detection of various environmental factors on the construction site usually only returns abnormal results, and the result feedback is single

Moreover, the computing cluster used for computing is easy to leak information and has low security performance

[0003] Therefore, the existing channel blocking detection technology has the problems of low detection accuracy and detection efficiency, single result feedback, and low security performance in the process of data processing and transmission.

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