Water Quality Monitoring and Prediction System Based on CNN-LSTM Model and STM32 Microcontroller
A water quality monitoring and prediction system has been designed to improve the efficiency of water quality management.To this end,a method based on the CNN-LSTM model was adopted.This model utilizes CNN to extract spatial features from water quality sen-sor data and passes the output sequence to the LSTM network to capture temporal information.This model that combines CNN and LSTM not only maintains efficiency but also has a simple structure,making it very suitable for deployment on STM32 microcontrollers,In the process of implementing sensor data collection,artificial intelligence processing of STM32,local display,and data uploading to the Lewei IoT cloud platform,this design can improve the efficiency of water quality management.
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