Design and Experimental Validation of a Low-Power IoT-Based Smart Irrigation System Using LoRa, ET0, and Crop Water Stress Index for Precision Agriculture
Abstract
Efficient irrigation management requires complementary information on atmospheric demand, soil conditions, and crop water stress. This study presents a low-power Internet of Things (IoT)-based irrigation system that integrates these components within a unified monitoring and control framework. The system combines LoRa communication, ESP32-based sensor nodes, soil and meteorological sensing, FAO-56 reference evapotranspiration (ET0), and canopy-temperature-based Crop Water Stress Index (CWSI). Irrigation decisions rely on the complementary use of ET0, in situ soil measurements, and CWSI rather than on a single indicator. A hybrid time-, event-, and query-driven acquisition strategy was implemented to adapt node activity and limit communication overhead. The system was deployed under outdoor conditions in Oujda, Morocco, demonstrating integrated sensing, wireless data transmission, crop-stress monitoring, and automated irrigation control. Energy characterization further showed distinct consumption profiles across sensing, communication, actuation, and low-power operating states, supporting the use of duty cycling to limit active node operation. The results demonstrate the feasibility of integrating environmental, soil, and crop-level information within a low-power IoT framework for adaptive irrigation management.
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BibTeX
@article{ayat2026design,
title = {{Design and Experimental Validation of a Low-Power IoT-Based Smart Irrigation System Using LoRa, ET0, and Crop Water Stress Index for Precision Agriculture}},
author = {Yassine Ayat and Ali El Moussati and Oumayma Rachdi and Maryem Dinar and Abdelaziz El Aouni and Hajar Karkri and Mohammed Benzaouia and Wiame Benzekri and Ismail Mir and Aumeur El Amrani and Abdelmalek Mimouni},
journal = {IoT},
year = {2026},
month = jul,
doi = {10.3390/iot7030059},
url = {https://hal.science/hal-05736703v1},
note = {CC BY},
}
RIS
TY - JOUR
TI - Design and Experimental Validation of a Low-Power IoT-Based Smart Irrigation System Using LoRa, ET0, and Crop Water Stress Index for Precision Agriculture
AU - Yassine Ayat
AU - Ali El Moussati
AU - Oumayma Rachdi
AU - Maryem Dinar
AU - Abdelaziz El Aouni
AU - Hajar Karkri
AU - Mohammed Benzaouia
AU - Wiame Benzekri
AU - Ismail Mir
AU - Aumeur El Amrani
AU - Abdelmalek Mimouni
PY - 2026
DA - 2026/07/27
JO - IoT
DO - 10.3390/iot7030059
UR - https://hal.science/hal-05736703v1
AB - Efficient irrigation management requires complementary information on atmospheric demand, soil conditions, and crop water stress. This study presents a low-power Internet of Things (IoT)-based irrigation system that integrates these components within a unified monitoring and control framework. The system combines LoRa communication, ESP32-based sensor nodes, soil and meteorological sensing, FAO-56 reference evapotranspiration (ET0), and canopy-temperature-based Crop Water Stress Index (CWSI). Irrigation decisions rely on the complementary use of ET0, in situ soil measurements, and CWSI rather than on a single indicator. A hybrid time-, event-, and query-driven acquisition strategy was implemented to adapt node activity and limit communication overhead. The system was deployed under outdoor conditions in Oujda, Morocco, demonstrating integrated sensing, wireless data transmission, crop-stress monitoring, and automated irrigation control. Energy characterization further showed distinct consumption profiles across sensing, communication, actuation, and low-power operating states, supporting the use of duty cycling to limit active node operation. The results demonstrate the feasibility of integrating environmental, soil, and crop-level information within a low-power IoT framework for adaptive irrigation management.
SN - 2624-831X
ER -