An Affordable Internet of Things Based Water Level Monitoring System for Alternate Wetting and Drying Irrigation Management in Paddy Cultivation

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.

Authors

Institutions

Publication Details

Journal
Turkish Journal of Agricultural Engineering Research
Published
2026-06-29
DOI
https://doi.org/10.46592/turkager.1855897
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Affordable Internet of Things Based Water Level Monitoring System for Alternate Wetting and Drying Irrigation Management in Paddy Cultivation

Mohammad Monjurul Alam, Surajit Sarkar, Joy Biswas
Turkish Journal of Agricultural Engineering Research
Smart Agriculture and AI
article

An Affordable Internet of Things Based Water Level Monitoring System for Alternate Wetting and Drying Irrigation Management in Paddy Cultivation

Mohammad Monjurul Alam, Surajit Sarkar, Joy Biswas
article en

Abstract

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.

Turkish Journal of Agricultural Engineering ResearchVol. 7(1)
Bangladesh Agricultural University (BD), Development Initiatives (GB)
Clean water and sanitation
Openalex Percentile: Top 10%
Smart Agriculture and AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.