A hierarchical early warning method for the concentration of air pollutants in smart agriculture

Abstract

The invention discloses a hierarchical early warning method for smart agricultural air pollution concentration, which belongs to the technical field of pollution monitoring. The invention can optimize the crop planting area on the basis of the difference in the sensitivity of different crops to the concentration of different types of air pollutants at different growth heights. The effective resource allocation of air pollutant concentration control and decision-making provides guarantee for the healthy growth of various crops in an environment of safe air pollutant concentration, and promotes the steady development of smart agriculture. The present invention proposes a method of using uniformly distributed unmanned aerial vehicles to lift and lower at a uniform speed in the target crop planting area to control the four atmospheric pollutants SO in the area. 2 , NO x , CO, O 3 The real-time discrete point sampling of concentration changes with height ensures the timeliness and accuracy of the measurement process to a certain extent, avoids the randomness and contingency of air pollutant concentration changes with height in different sub-regions, and is conducive to the intelligence of agricultural planting. management and control.

Description

technical field [0001] The invention belongs to the technical field of pollution monitoring, and relates to crop-oriented air pollutant concentration prediction, in particular to a hierarchical early warning method for smart agricultural air pollutant concentration. Background technique [0002] As the latest development direction of agricultural production, smart agriculture integrates emerging cloud computing, Internet of Things, big data and other technologies based on the agricultural production environment, and realizes intelligent perception, intelligent early warning, intelligent decision-making, and intelligent analysis of the agricultural production process. Agricultural production provides guidance. At present, smart agriculture has achieved important breakthroughs in the field of automatic monitoring of various environmental factors such as soil moisture, ambient temperature and humidity, and light intensity. Based on the real-time collection and monitoring of the...

AI Technical Summary

Problems solved by technology

At present, smart agriculture has achieved important breakthroughs in the field of automatic monitoring of various environmental factors such as soil moisture, ambient temperature and humidity, and light intensity. Based on the real-time collection and monitoring of the above-mentioned natural factors closely related to crop growth based on sensor nodes widely distributed in agricultural production areas , and analyze the data collected by multiple factors to provide decision-making basis for automatic irrigation, automatic cooling, automatic fertilization and other control methods in the agricultural park, but the system has not yet realized the SO 2 , NO x , CO, O 3 Hierarchical short-term prediction of the sensitivity difference of various air pollution sources, such as single fixed sampling point measurement method has very large randomness and contingency

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