Raman spectroscopy has been widely used in the field of environmental protection. In order to accurately judge the scattering signal and spectrum of water pollutants, this paper uses the artificial neural network method to quickly identify the Raman spectrum of water pollutants, which provides a good scheme for rapid and intelligent identification of Raman spectrum. Through real-time monitoring of water pollution, not only the detection speed of water pollution is greatly improved, but also the rapid decision to prevent and control water pollution is made, It is of great significance to take corresponding measures. In this paper, a RS system for water quality monitoring (WQM) is designed based on ANN. It is verified that the system has high detection accuracy through pH detection of water quality, and the ANN model can accurately classify water quality categories.

Huitae Lee. Artificial Neural Network Based Raman Spectroscopy System for Water Quality Monitoring. Water Pollution Prevention and Control Project (2022), Vol. 3, Issue 3: 28-36. https://doi.org/10.38007/WPPCP.2022.030304.

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