AI-Driven LoRaWAN-Based Smart Irrigation System Using IoT for Sustainable Water Management in Semi-Arid Regions
Rahima NOUASSE, Younes BENHOURIA, Said BENHLIMA
Abstract. Sustainable agriculture depends heavily on efficient water management, particularly in semi-arid regions such as Morocco, recurring droughts and the progressive depletion of groundwater resources increasingly crop productivity. Accordingly, this paper presents the design and experimental evaluation of a low- cost, AI-driven IoT irrigation architecture that combines environmental sensing, long-range connectivity, and intelligent decision-making. The system employs a Raspberry Pi 4 as an edge node, leverages LoRaWAN network to ensure reliable long-distance data transmission, and incorporates meteorological station monitoring temperature, humidity, wind, rainfall, solar radiation, and soil-moisture. In addition, the collected field data are processed locally and subsequently presented through interactive dashboards for rapid interpretation. Experimental results show that the system-maintained soil moisture within the agronomically desirable band between the wilting point and field capacity, reducing water consumption by 27 % and lowered energy use by 18 % compared with traditional irrigation. The LoRaWAN link achieved 98.6 % data success, confirming robust performance in rural conditions. Powered by solar energy, this framework becomes both economically accessible and environmentally sustainable, making it well-suited to small and medium-scale farms. Furthermore, the implemented hybrid LSTM-DNN model achieved an R² of 0.93 and RMSE of 0.7 mm/day, demonstrating high accuracy in predicting evapotranspiration and irrigation needs. Finally, by adopting a solar-powered energy, the proposed framework offers an affordable and scalable solution for small and medium-sized agricultural holdings and farms.
Keywords
IoT, Smart Irrigation, Machine Learning, Precision Agriculture, Sustainable Water Management, Soil Moisture, Renewable Energy
Published online 4/25/2026, 7 pages
Copyright © 2026 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Rahima NOUASSE, Younes BENHOURIA, Said BENHLIMA, AI-Driven LoRaWAN-Based Smart Irrigation System Using IoT for Sustainable Water Management in Semi-Arid Regions, Materials Research Proceedings, Vol. 64, pp 284-290, 2026
DOI: https://doi.org/10.21741/9781644904091-35
The article was published as article 35 of the book Energy Futures
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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