Edge-Computing Smart Irrigation Controller Using LoRaWAN and LSTM for Predictive Controlled Deficit Irrigation – PMC

approaches and technologies used, and the positive results that studies have shown, there are several aspects that could be investigated in greater depth. These approaches can integrate edge computing to enhance real-time monitoring and control of DI in almond orchards, optimizing water use through AI-driven sensor data processing at the field level. By processing data locally, edge computing reduces latency, enabling faster and more precise irrigation adjustments based on environmental conditions. Combining AI algorithms with soil moisture and climate can optimize water distribution, minimize

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12656048/