Real-Time Calibration Method of Air Quality Data Based on AdaBoost Training Model

Abstract

At present, a large number of cities are facing the situation of "garbage besieged", and the existing garbage disposal system can no longer meet the increasingly complex factors. With the development of a new generation of Internet of Things technology, integrating the knowledge and technology of related disciplines such as network and geographic information, it is possible to build a real-time monitoring platform for seepage and odor in landfills to complete gas monitoring. The author of the paper reviewed the related technologies of the Internet of Things, and proposed the design scheme of the online monitoring system for odor and seepage of the Maiyuan garbage dump in Nanchang City, selected 5 monitoring items, completed the data collection, and used the collected data to use Matlab and python software to carry out simulation analysis and prediction, and finally discuss the main factors and treatment measures of environmental pollution, provide theoretical guidance for relevant managers to improve the overall management decision-making level of urban domestic garbage dumps, and draw some practical conclusions.