Light intensity monitoring system for pineapple seedling based on Kalman filter algorithm

In order to reduce the error and lag time of light intensity monitoring in the process of pineapple seedling growing, a light intensity monitoring system based on Kalman filter algorithm was designed. Based on the construction of LoRa wireless communication and embedded data acquisition terminal, a visual and online monitoring software interface with display and storage functions was developed, and a Kalman filter model was proposed. Through comparative experiments, it was concluded that the Kalman filter model was superior to the weighted recursive average filter model. The MAE percentage was not more than 0.13%, the RMSE percentage was not more than 0.16%, and the lag time was not more than 1 s. The results showed that the monitoring system had low error and lag time, which was of guiding significance for the precise regulation of light in pineapple seedling.