A method for intelligent aggregation of spatio-temporal data

Abstract

The present invention belongs to the field of cross-combination of multi-disciplines and technologies. 1. Data acquisition. The monitoring station uses gas sensors to monitor sulfur dioxide and nitrogen dioxide in the air in real time, and passes the monitored concentrations of nitrogen dioxide and sulfur dioxide through the data acquisition system The application program interface in the data input; second, model analysis; third, interpolation calculation; fourth, online data fusion, select the complete data set after interpolation as the sample data, use the sample data to carry out the offline prediction simulation of the spatio-temporal data model, use The forgetting factor recursive algorithm realizes the online prediction of nitrogen dioxide and sulfur dioxide concentration data; the gas-sensing material of the gas sensor used in the monitoring station is a double-layer graphene / graphite phase carbon nitride / tin oxide sensor, which has a high response sensitivity and relatively The low detection limit greatly improves the accuracy of data collection, making the real-time online prediction of sulfur dioxide and nitrogen dioxide more accurate.

Description

technical field [0001] The invention belongs to the field of cross-combination of multiple disciplines and technologies, and in particular relates to an intelligent aggregation method of spatio-temporal data. Background technique [0002] Sulfur dioxide and nitrogen dioxide are the main pollutants in the atmosphere. With the rapid development of urbanization and the continuous expansion of the scale of transportation in my country, a large amount of sulfur dioxide and nitrogen dioxide that are harmful to the environment are discharged into the atmosphere, causing serious air pollution. Not only It has brought great harm to the earth environment on which we live, and even threatened the health of human beings. It is of great practical significance to predict sulfur dioxide and nitrogen dioxide. [0003] Although the existing methods for aggregating and predicting sulfur dioxide and nitrogen dioxide data can realize the prediction of nitrogen dioxide and sulfur dioxide to a cer...

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Problems solved by technology

[0003] Although the existing methods for aggregating and predicting sulfur dioxide and nitrogen dioxide data can realize the prediction of nitrogen dioxide and sulfur dioxide to a certain extent, due to the low response sensitivity of the sensor during the data collection process of sulfur dioxide and nitrogen dioxide, the detection The high lower limit concentration greatly affects the accuracy of data collection, which makes the prediction of sulfur dioxide and nitrogen dioxide inaccurate. In order to improve the sensor response sensitivity and reduce the lower limit of detection, people solve these problems by changing the gas-sensitive material, which is the core component of the gas sensor. problem, but existing sensors often prepare single-layer graphene as a gas-sensing material, but due to the lack of dangling bonds and zero bandgap width of single-layer graphene, the gas-sensing material prepared by graphene is not ideal, and the existing Another gas-sensing material made of metal oxide requires a higher temperature to respond to the detected gas, and both gas-sensing materials made of graphene and metal oxide have a high detection limit for sulfur dioxide and nitrogen dioxide. low response sensitivity

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