This invention discloses an
artificial intelligence-based method and
system for controlling the amount of liquid
fertilizer drip irrigation in agricultural planting. The method involves collecting multi-source datasets through a multimodal sensing network; fusing the multi-source datasets using a STAFN spatiotemporal attention fusion network to obtain a fused dataset; establishing a dual-channel demand prediction model, inputting the fused dataset into the model, and outputting prediction results; calculating the
fertilizer concentrate
mixing ratio based on the prediction results; adjusting the
fertilizer absorption rate of the Venturi fertilizer applicator according to the fertilizer concentrate
mixing ratio using a
fuzzy PID control algorithm; dividing the planting area into several intelligent
irrigation zones; and implementing differentiated fertilization for each zone using a pulse
drip irrigation strategy. This method adapts to the differences in soil and crops in different regions, improving
drip irrigation efficiency and accuracy.