Sanitary emergency monitoring method and system in heavy pollution weather

By combining fixed sanitary monitoring points and drone flight paths in heavy pollution weather, using the improved ConvLSTM model for data prediction, the problem of inability to cover monitoring blind spots in traditional monitoring methods is solved, and the coverage and prediction accuracy of sanitary emergency monitoring are improved.

CN119692633AActive Publication Date: 2025-03-25CHENGDU CENT FOR DISEASE CONTROL & PREVENTION
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Patent Information

Application Number
CN202510214874.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-26
Publication Date
2025-03-25
Estimated Expiration
2045-02-26

AI Technical Summary

Technical Problem

Traditional health regional monitoring methods rely on fixed monitoring sites and lack dynamic scheduling capabilities, resulting in the inability to cover monitoring blind spots in time, especially in scenarios where pollution spread rapidly changes, there is a significant lag in data collection.

Method used

Full coverage of the target area is achieved by pre-setting multiple fixed sanitary monitoring points and combining with the drone flight path. The improved ConvLSTM model is used to predict pretreated health monitoring data to improve the prediction accuracy of pollutant propagation paths.

Benefits of technology

It has achieved effective coverage of sanitation emergency monitoring in heavy pollution weather, improved the accuracy of predicting pollutant transmission paths, and thus enhanced the auxiliary effect of sanitation emergency.

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Abstract

The invention discloses a health emergency monitoring method and system in heavy pollution weather, and relates to health emergency, data processing and artificial intelligence, and the method comprises the steps: building a map mark of a target region on a corresponding region map according to the position of each health monitoring point; determining a possible monitoring blind area; according to the possible monitoring blind area, the flight path of the unmanned aerial vehicle is configured; under the condition that the index of the weather monitoring data exceeds a prediction threshold value, health monitoring data covering a target area is obtained from a health monitoring point and a configuration-based unmanned aerial vehicle; preprocessing the health monitoring data, and utilizing an improved ConvLSTM model to predict future possible health event distribution according to the preprocessed health monitoring data; and according to a prediction result, carrying out grading marking based on the regional map, and executing a corresponding health emergency strategy on the graded and marked region. The method provided by the invention can effectively improve the auxiliary management effect of health emergency.
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