Design and Implementation of Interactive PyQt5-Based Air Pollutant Spectral Analysis Software

Abstract

Air pollution is an important issue in the environmental field. To control air pollution, it is particularly critical to clarify the composition of air pollutants in corresponding areas. Using atmospheric spectral data and machine learning methods, the composition of pollutants in the atmosphere can be quickly predicted. This process requires the processing of a large amount of spectral data and file management. In response to these requirements, multiple functional interfaces were designed in this work, and interface development and logic writing were carried out by combining the QT designer with code. Data management was carried out in combination with the MySQL database, and spectral diagrams were drawn in combination with the Matplotlib library. Interactive air pollution analysis software based on PyQt5 was created. The software can realize data storage, retrieval, modification, and deletion and facilitate the processing and visualization of a large amount of spectral data. Combined with the model of spectral component prediction and concentration identification, the corresponding interactive operation can be realized.