International Journal of Advanced Engineering Application

LSTM-Driven IoT Smart Irrigation Controller for Sugarcane Belts: Field Validation and Water-Yield Trade-off Analysis

Author(s):Aditya N. Yadav

Affiliation: Dept. of Agri. Engineering Krishna Valley Institute of Technology, Karad (MS)

Page No: 13-16

Volume issue & Publishing Year: Volume 3, Issue 5, 2026/05/06

Journal: International Journal of Advanced Engineering Application (IJAEA)

ISSN NO: 3048-6807

DOI: https://doi.org/10.5281/zenodo.20068811

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Abstract:
Drip irrigation in sugarcane plots of Western Maharashtra suffers from over-application due to fixed-timer schedules. This work presents a low-cost ESP32-based IoT node coupled with a Long Short-Term Memory (LSTM) forecasting model that predicts soil volumetric water content (VWC) six hours ahead and gates a solenoid drip valve through a two-stage decision rule that also consults a 6-hour rainfall forecast. A pilot was deployed on a 0.4-hectare plot in Karad taluka for an 8-week vegetative period. Compared with the conventional timer schedule, the proposed controller cut water consumption by 45.1% (720 → 395 L/m²) while raising the relative yield index by 9.2%. The LSTM achieved RMSE = 1.62% VWC and R² = 0.96 against the held-out test set, outperforming ARIMA, SVR, and MLP baselines. Hardware bill of materials is below ₹4,200, supporting replication by smallholder cooperatives.

Keywords: smart irrigation, LSTM, IoT, ESP32, soil moisture forecasting, sugarcane.

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