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A visual early warning method and system for traffic emission pollution

A technology for traffic and traffic intersections, which is applied in the field of traffic emission pollution visualization early warning methods and systems, can solve the problems of single data source, single means, and difficulty in effectively predicting the concentration of air pollutants, and achieves good practicability and high reliability. Effect

Active Publication Date: 2021-06-15
CENT SOUTH UNIV
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the current early warning means are single, and the source of the early warning data is the data source of the fixed air quality monitoring station. Pollutant concentration is difficult to achieve effective prediction

Method used

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  • A visual early warning method and system for traffic emission pollution
  • A visual early warning method and system for traffic emission pollution
  • A visual early warning method and system for traffic emission pollution

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Embodiment Construction

[0079] Such as figure 1 Shown is a schematic flow chart of the method of the present invention: the traffic discharge pollution visualization early warning method provided by the present invention includes the following steps:

[0080] S1. Randomly move and monitor in the monitoring area, obtain the location data information of the monitoring point, the air data of the monitoring point and the basic data information of the monitoring area; specifically, use an air quality monitoring vehicle to conduct random monitoring in the monitoring area in a mobile manner Mobile, and collect mobile air quality data at the location of the air quality monitoring vehicle, record the location information of the air quality monitoring vehicle when collecting mobile air quality data, and record the location information and fixed air quality data of the air quality monitoring station in the monitoring area; At the same time, obtain real-time weather data information and wind direction data infor...

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Abstract

The invention discloses a traffic discharge pollution visualization early warning method, which includes the basic data information of the monitoring area; extracts the characteristics of the relative position information; selects the optimal air quality monitoring station and the optimal traffic road node; constructs the prediction of air pollutants model; build a pollutant concentration prediction model for any monitoring point and correct it; perform visual early warning of urban traffic pollution emissions in the monitoring area. The invention also discloses a system for realizing the traffic discharge pollution visualization early warning method. The method of the invention can perform real-time prediction and early warning of real-time dynamic air pollutants at any point in the road traffic coverage area, and the method of the invention has high reliability and good practicability.

Description

technical field [0001] The invention specifically relates to a visual early warning method and system for traffic discharge pollution. Background technique [0002] In recent years, with the deepening of industrialization and urbanization and the increasing popularity of private cars, the problem of air pollution in my country has become increasingly serious. The air quality is deteriorating day by day, which has an important impact on the health of urban residents and the economic development of society. With the increasing popularity of intelligent algorithms such as machine learning and deep neural networks, the use of intelligent algorithms to predict air pollutants based on environmental big data has great potential in assisting relevant departments in decision-making, improving environmental protection efficiency, controlling the spread of pollutants, and realizing industrial regulation. important value. In the area covered by urban roads, exhaust emissions during ve...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N33/00G08B21/12G06K9/62G06N3/00
CPCG01N33/0063G08B21/12G06N3/006G06F18/2411G01N33/0068Y02A50/20
Inventor 刘辉李燕飞刘泽宇
Owner CENT SOUTH UNIV
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