Water Level Monitoring System for Sustainable Rice Cultivation based on Alternative Wetting-and-Drying Technique

This article presents the development of an IoT system for monitoring water level for rice cultivation based on the alternate wetting-and-drying (AWD) technique, which is recognized for saving water and reducing methane emissions, a greenhouse gas contributing to global warming. The system comprises water level sensing devices (WaLSenses) that measure and send the water levels in rice fields to our gateway via LoRa technology. The data is then uploaded to the cloud system, enabling farmers to monitor and receive smartphone notifications when the water level reaches the specified point for pumping water into the fields. The practical use showed that the water level is accurately measured with a 4.06cm offset, and the data can be transmitted even when the sensing device is 234 meters away from the gateway. Future developments include a pump control device to control the water levels according to the AWD technique automatically, extend the LoRa coverage to cover larger areas, and create an AI platform that can analyze, predict and assist the water resource management in Thailand.

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Publication Details

Published
2024-10-01
DOI
https://doi.org/10.1109/r10-htc59322.2024.10778900
Citations
1
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.60
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Water Level Monitoring System for Sustainable Rice Cultivation based on Alternative Wetting-and-Drying Technique

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Abstract

This article presents the development of an IoT system for monitoring water level for rice cultivation based on the alternate wetting-and-drying (AWD) technique, which is recognized for saving water and reducing methane emissions, a greenhouse gas contributing to global warming. The system comprises water level sensing devices (WaLSenses) that measure and send the water levels in rice fields to our gateway via LoRa technology. The data is then uploaded to the cloud system, enabling farmers to monitor and receive smartphone notifications when the water level reaches the specified point for pumping water into the fields. The practical use showed that the water level is accurately measured with a 4.06cm offset, and the data can be transmitted even when the sensing device is 234 meters away from the gateway. Future developments include a pump control device to control the water levels according to the AWD technique automatically, extend the LoRa coverage to cover larger areas, and create an AI platform that can analyze, predict and assist the water resource management in Thailand.

Rajamangala University of Technology (TH), Ministry of Agriculture and Cooperatives (TH)
Zero hunger
Openalex Percentile: Top 20%
Smart Agriculture and AI
0.60
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