A 5g communication engineering intelligent detection system

Abstract

The invention discloses a 5G communication engineering intelligent detection system. The system mainly includes a storage module, a central control module, an emergency processing module, a data acquisition module, a preprocessing module, and a detection and analysis module. The data acquisition module collects safety data information on expressways , the preprocessing module analyzes and processes the security data information to obtain preprocessed data, and sends the preprocessed data to the detection and analysis module, and the detection and analysis module uses the logistic regression algorithm to perform security prediction on the first type of data information and the second type of data information respectively Obtain the first prediction result and the second prediction result, and send the prediction result to the central control module. The central control module first judges the first prediction result and the second prediction result to obtain the final prediction result, and then judges the final prediction result , improve the accuracy of safety prediction during high-speed operation, increase the speed of detection, thereby reducing the occurrence of accidents.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to an intelligent detection system for 5G communication engineering. Background technique [0002] With the continuous development of 5G communication technology, it has also been widely used in the field of transportation technology, especially the safe operation monitoring of expressways. Traffic accidents, when encountering extreme weather such as heavy rain, heavy fog, and heavy snow, the intersection of the expressway will be prohibited to avoid traffic accidents when the vehicle is driving on the expressway, but when the vehicle encounters sudden extreme weather on the expressway, the vehicle will only It can slow down or stop on the expressway. When the extreme weather eases, the vehicle will leave the expressway nearby. Although the traffic police can make the vehicle leave the expressway safely, it will waste a lot of high-speed road users and expressway management p...

AI Technical Summary

Problems solved by technology

[0002] With the continuous development of 5G communication technology, it has also been widely used in the field of transportation technology, especially the safe operation monitoring of expressways. Traffic accidents, when encountering extreme weather such as heavy rain, heavy fog, and heavy snow, the intersection of the expressway will be prohibited to avoid traffic accidents when the vehicle is driving on the expressway, but when the vehicle encounters sudden extreme weather on the expressway, the vehicle will only It can slow down or stop on the expressway. When the extreme weather eases, the vehicle will leave the expressway nearby. Although the traffic police can make the vehicle leave the expressway safely, it will waste a lot of high-speed road users and expressway management personnel. time and energy; extreme weather will also reduce the accuracy of the information collected by the highway monitoring system, making the images captured by the monitoring unclear, although there are already many high-tech cameras with infrared night vision devices that can improve the accuracy of collection However, high-tech products have not been fully popularized, and different extreme weather has different impacts on different expressway sections; in addition to weather, there are other factors such as traffic flow that affect the safety of expressways. The regression model can be used to analyze the prediction and evaluation of the real-time accident risk of the expressway, but the regression model also has its own limitations. The accuracy of the prediction model is affected by the data. If the problems are not timely and the factors considered are different, there will be deviations in the forecast results, which will lead to a decrease in the accuracy of the forecast, which will cause safety problems. The forecast results of the forecast model lack comparison standards, and the accuracy of the results cannot be accurately predicted.

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