Real-time monitoring system of temporal and spatial distribution of air pollutant concentration on urban road network

Abstract

The invention relates to a real-time monitoring system of temporal and spatial distribution of air pollutant concentration on urban road network, including a data center and a sensor network. The sensor network includes a plurality of sensors distributed on urban road network. Formed by a plurality of sensors, the real-time monitoring data are transmitted to the data center which combines with the data from external databases. The external databases consist of a vehicle information database, a vehicle annual inspection database, a geographic information database of the urban road network, and an urban air pollutant monitoring database. The data are fused by a self-tuning asynchronous complementary filtering algorithm. The precise real-time monitoring of temporal and spatial distribution of air pollutant concentration is finally achieved. The real-time monitoring system of temporal and spatial distribution of air pollutant concentration on urban road network has the advantages of using all kinds of existing traffic sensors on roads without adding extra equipment, achieving a precise real-time monitoring of temporal and spatial distribution of air pollutant concentration by means of an atmospheric modeling and the data fusion technology, and providing data support for legislating pollution control policies.

Description

technical field [0001] The invention relates to a real-time monitoring system for temporal and spatial distribution of air pollutant concentration in urban road network, which belongs to the real-time monitoring technology of air pollution Background technique [0002] With the increase of urban motor vehicle ownership and the removal of industrial pollution sources, motor vehicle exhaust emissions have gradually become the main source of urban air pollution. A large number of studies have shown that residents living in living areas close to main roads, Among the exhaust pollution, the probability of suffering from asthma, tuberculosis and various cardiovascular and cerebrovascular diseases will be greatly increased. Therefore, if the temporal and spatial distribution of air pollutant concentrations in the urban road network can be obtained in real time, it will be of great help to formulate relevant policies for pollution control. However, due to factors such as the huge u...

AI Technical Summary

Problems solved by technology

Due to the complexity and impreciseness of the diffusion model, only an approximate contamination situation can be obtained

Using neural network model, minimum variance model and autoregressive model to identify the relationship between existing data and concentration is a more accurate method, but since each street needs to do experiments in advance to determine this mathematical relationship, And it needs to be corrected regularly, the practicality of this method is not very strong

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