Pillai et al. Res. Trends Int. J. Technol. Innov., January - March 2026, 1 (1) : 19-26
1Department of Farm Machinery and Power Engineering, Tamil Nadu Agricultural University, Coimbatore, India; 2Department of Electronics Engineering, PSG College of Technology, Coimbatore, India
Article History
Accepted : 25 Feb 2026
Published : 28 Mar 2026
Publication Issue
Volume 1, Issue 1
January - March 2026
Page Number19–26
Water scarcity in semi-arid farming regions demands irrigation systems that respond to real soil conditions rather than fixed schedules. This paper describes a LoRaWAN-based sensor network that measures soil moisture, temperature and electrical conductivity at three depths and triggers solenoid valves through a rule-based edge controller. Field trials across 4 hectares of groundnut cultivation over one growing season showed a 34 percent reduction in water consumption compared with conventional scheduled irrigation, with no significant yield penalty, while the battery-powered nodes operated for over eight months on a single charge.
Keywords - LoRaWAN, precision agriculture, smart irrigation, soil moisture sensing, low-power IoT
Conventional irrigation scheduling in water-stressed regions often ignores real-time soil conditions, leading to either water wastage or crop stress. Low-power wide-area network technologies such as LoRaWAN make continuous field-scale sensing economically viable for smallholder farms.
Twelve sensor nodes measuring soil moisture, temperature and electrical conductivity at 15cm, 30cm and 45cm depths were deployed across a 4-hectare groundnut field and connected via a LoRaWAN gateway to a cloud dashboard. An edge controller applied threshold-based rules derived from crop water stress coefficients to actuate solenoid valves, with performance compared against an adjacent plot under conventional calendar-based irrigation.
The LoRaWAN plot consumed 34 percent less irrigation water over the season while yield differed by less than 3 percent from the control plot, a statistically insignificant difference (p=0.41). Median packet delivery ratio across the 900m field span was 96.2 percent, and sensor nodes averaged 8.3 months of operation on a single 3.7V 6000mAh battery.
The results confirm that LoRaWAN-based sensing can materially reduce irrigation water use without compromising yield, offering a scalable option for resource-constrained farms. Future work will incorporate satellite-derived evapotranspiration estimates to refine the rule engine.
[1] Vasisht D. et al., FarmBeats: An IoT platform for data-driven agriculture, NSDI, 2017. [2] Ferrandez-Pastor F. J. et al., Precision agriculture design using wireless sensor networks, Computers and Electronics in Agriculture, 2016. [3] Foukalas F. et al., Coverage and capacity analysis of LoRaWAN, IEEE IoT Journal, 2019. [4] Kamienski C. et al., Smart water management platform, Sensors, 2019.
© 2026 The Author(s). Published by IJEIA Editorial Office. This is an open access article under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
Ramesh Chandra Pillai, Sowmya Balakrishnan (2026). A Low-Power LoRaWAN-Based Smart Irrigation Framework for Precision Agriculture in Semi-Arid Regions. IJEIA, 1(1), 19-26.
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