Implementation of a Wireless Sensor Network for Agro-Environmental Monitoring and Growing Degree Day-Based Rice Growth Assessment

This study presents a low-cost wireless sensor network (WSN) integrated with an Internet of Things (IoT) platform for continuous monitoring of agro-environmental parameters relevant to rice harvest decision support. Solar-powered sensor nodes equipped with temperature-humidity (DHT22) and light intensity (BH1750) sensors were deployed in a Pathum Thani 1 rice field in Si Prachan, Suphan Buri province, Thailand. Environmental data were recorded hourly from June to September 2025 and transmitted wirelessly to a cloud-based dashboard for real-time visualization. Growing Degree Days (GDD) were calculated from measured air temperature using a literature-based base temperature, and cumulative GDD (CGDD) was used to track rice growth progression across vegetative, reproductive, and grain-filling stages. The system demonstrated stable long-term operation and continuous data acquisition under field conditions. Observed CGDD trends were consistent with reported growth-stage thresholds for the studied rice variety, while measured light intensities ranged from 36,900 to 37,810 lx, relative humidity remained consistently high throughout the season, and air temperatures varied between daily minima of 23.5–25.2 °C and maxima near 35.4 °C, which are suitable for rice photosynthesis and development. The seasonal CGDD increased linearly to 580.3, 1189.9, 1593.7, and 2385.7 °C by the end of June, July, August, and September, respectively, exhibiting a strong linear relationship with days after 1 June 2025 (R2 = 0.9999), which confirms stable thermal accumulation throughout the growing season.

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Publication Details

Journal
Eng—Advances in Engineering
Published
2026-02-11
DOI
https://doi.org/10.3390/eng7020082
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

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article

Implementation of a Wireless Sensor Network for Agro-Environmental Monitoring and Growing Degree Day-Based Rice Growth Assessment

Ekkachaï Martwong, Patiwat Boonma, Wichai Nramat, Krittanai Thararattanasuwan et al.
Eng—Advances in Engineering
Remote Sensing in Agriculture
article

Implementation of a Wireless Sensor Network for Agro-Environmental Monitoring and Growing Degree Day-Based Rice Growth Assessment

Ekkachaï Martwong, Patiwat Boonma, Wichai Nramat, Krittanai Thararattanasuwan, Wasakorn Traiphat, Ongard Thiabgoh, Ekawit Songkroh
article en

Abstract

This study presents a low-cost wireless sensor network (WSN) integrated with an Internet of Things (IoT) platform for continuous monitoring of agro-environmental parameters relevant to rice harvest decision support. Solar-powered sensor nodes equipped with temperature-humidity (DHT22) and light intensity (BH1750) sensors were deployed in a Pathum Thani 1 rice field in Si Prachan, Suphan Buri province, Thailand. Environmental data were recorded hourly from June to September 2025 and transmitted wirelessly to a cloud-based dashboard for real-time visualization. Growing Degree Days (GDD) were calculated from measured air temperature using a literature-based base temperature, and cumulative GDD (CGDD) was used to track rice growth progression across vegetative, reproductive, and grain-filling stages. The system demonstrated stable long-term operation and continuous data acquisition under field conditions. Observed CGDD trends were consistent with reported growth-stage thresholds for the studied rice variety, while measured light intensities ranged from 36,900 to 37,810 lx, relative humidity remained consistently high throughout the season, and air temperatures varied between daily minima of 23.5–25.2 °C and maxima near 35.4 °C, which are suitable for rice photosynthesis and development. The seasonal CGDD increased linearly to 580.3, 1189.9, 1593.7, and 2385.7 °C by the end of June, July, August, and September, respectively, exhibiting a strong linear relationship with days after 1 June 2025 (R2 = 0.9999), which confirms stable thermal accumulation throughout the growing season.

Eng—Advances in EngineeringVol. 7(2)
Rajamangala University of Technology Suvarnabhumi (TH), Ubon Ratchathani University (TH)
Rajamangala University of Technology Suvarnabhumi
Openalex Percentile: Top 63%
Remote Sensing in Agriculture
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