Rice is the staple food for over 3.5 billion people globally. The increasing demand for freshwater and declining resource availability pose serious challenges to paddy production. Alternate Wetting and Drying (AWD) is a proven irrigation technique that can reduce water use, but manual monitoring limits its adoption. This study presents the development and preliminary validation of an affordable IoT-based AWD monitoring prototype designed to automate water level monitoring in paddy fields. The system uses sensor probes connected to a solar-powered, Wi-Fi-enabled microcontroller and transmits real-time water level data to a cloud database accessible through a dedicated Android application, allowing farmers to monitor and manage irrigation remotely. Under controlled test conditions, the system achieved 100% water level classification accuracy across 30 observations (95% CI: 88.6%–100%, Wilson score interval), correctly categorizing all water levels into predefined High, Low, and Very Low statuses. The Very Low class was represented by only two observations, and all results should be interpreted cautiously pending long-term multi-season field validation. The total system cost is USD 42, making it potentially accessible to smallholder farmers. Benefits such as water savings, greenhouse gas emission reduction, and labor reduction are consistent with published AWD literature but were not directly measured in this study and require confirmation through future comparative field trials.
Sarkar et al. (Mon,) studied this question.