Intelligent monitoring method of atmospheric environment based on STM32 single-chip microcomputer

Under the background of the development of artificial intelligence, computer technology has gradually been applied to atmospheric environment monitoring. However, the existing intelligent monitoring and analysis methods for the atmospheric environment have problems such as low degree of automation, long detection time, and low analysis accuracy. To solve these problems, the research proposes an intelligent monitoring and analysis method for the atmospheric environment based on the STMicroelectronics 32-bit series microcontroller chip (STM32) single-chip microcomputer. The research first built a data acquisition system based on the STM32 single-chip microcomputer, and combined with the improved empirical mode decomposition method to pre-process the collected data. After processing, the study utilized the Pearson correlation coefficient analysis method to screen out the signal data with higher contribution, and input them into the prediction model based on the long short-term memory network for prediction analysis. The experiment findings denote that in the practical application of the method proposed in the study, the values of its prediction accuracy, average absolute percentage error and determination coefficient index are 98.45%, 0.03 and 0.04 respectively. Moreover, the data utilization rate of the monitoring data is as high as 99.72%, which is more than 5% higher than that of other methods. Its response time is only 0.63 seconds, which has a relatively high computational efficiency. The proposed method in the research can effectively enhance the real-time performance and accuracy of atmospheric environment monitoring, providing strong technical support for environmental protection.