Artificial intelligence (AI) is reshaping irrigation management across Europe by integrating machine-learning forecasts, satellite and uncrewed aerial vehicle (UAV) observations, and Internet of Things (IoT) sensor networks. Reported water savings commonly range from 20% to 40%, but effects depend on crop, climate, irrigation method, baseline practice, and validation design [1]. Applications now span open-field crops, protected cultivation, and urban green spaces. Wider deployment is constrained by fragmented datasets and platforms, limited interoperability, high initial and maintenance costs, uneven rural connectivity, shortages of digital skills, and inconsistent policy support.
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