Aqualyze: Smart Monitoring Water Quality through IoT-Enabled Sensors in RAS

Mangrove crab ( Scylla serrata ) cultivation faces challenges in maintaining optimal water quality, which is crucial for their health and growth. Traditional water quality monitoring methods can be labor-intensive and provide only intermittent data. This research presents "Aqualyze," an Internet of Things (IoT)-based system designed for smart, real-time monitoring of water quality in Recirculating Aquaculture Systems (RAS) for mangrove crab cultivation. The Aqualyze system employs sensors to continuously measure key parameters: water temperature (DS18B20), pH (4502C), dissolved oxygen (DO) (SEN0237), and turbidity (TS-300B). Data gathered by these sensors is processed by an ATmega328P microcontroller integrated with an ESP8266 Wi-Fi module. The processed data is then transmitted via the MQTT protocol to a HiveMQ broker and subsequently stored in a Firestore database for logging and analysis. Real-time monitoring results are displayed on an LCD I2C and can be accessed by users via a LINE bot, which provides alerts and on-demand data. The result of testing showed that while pH (7.1–8.1) and temperature (28.50–28.80 °C) remained within acceptable ranges, dissolved oxygen was consistently low (2.1–3.0 ppm), and turbidity fluctuated significantly with occasional sensor errors due to improper placement. This system aims to provide aquaculture operators with timely and accurate water quality information, enabling proactive management and potentially improving crab survival and yield.

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Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.08.302
Citations
1
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.82
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article

Aqualyze: Smart Monitoring Water Quality through IoT-Enabled Sensors in RAS

Violitta Yesmaya, Jun-Xian Teng, Evawaty Tanuar, Jeremy Sean Sitranata et al.
1 citations
Procedia Computer Science
Water Quality Monitoring Technologies
0.82
article

Aqualyze: Smart Monitoring Water Quality through IoT-Enabled Sensors in RAS

Violitta Yesmaya, Jun-Xian Teng, Evawaty Tanuar, Jeremy Sean Sitranata, Ignasius Holy Prasetya, Roikhanatun Nafi’ah, Suzana Ariff Azizan
article en
1 citations

Abstract

Mangrove crab ( Scylla serrata ) cultivation faces challenges in maintaining optimal water quality, which is crucial for their health and growth. Traditional water quality monitoring methods can be labor-intensive and provide only intermittent data. This research presents "Aqualyze," an Internet of Things (IoT)-based system designed for smart, real-time monitoring of water quality in Recirculating Aquaculture Systems (RAS) for mangrove crab cultivation. The Aqualyze system employs sensors to continuously measure key parameters: water temperature (DS18B20), pH (4502C), dissolved oxygen (DO) (SEN0237), and turbidity (TS-300B). Data gathered by these sensors is processed by an ATmega328P microcontroller integrated with an ESP8266 Wi-Fi module. The processed data is then transmitted via the MQTT protocol to a HiveMQ broker and subsequently stored in a Firestore database for logging and analysis. Real-time monitoring results are displayed on an LCD I2C and can be accessed by users via a LINE bot, which provides alerts and on-demand data. The result of testing showed that while pH (7.1–8.1) and temperature (28.50–28.80 °C) remained within acceptable ranges, dissolved oxygen was consistently low (2.1–3.0 ppm), and turbidity fluctuated significantly with occasional sensor errors due to improper placement. This system aims to provide aquaculture operators with timely and accurate water quality information, enabling proactive management and potentially improving crab survival and yield.

Procedia Computer ScienceVol. 269
Binus University (ID), University of Malaya (MY)
Openalex Percentile: Top 21%
Water Quality Monitoring Technologies
0.82
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Aqualyze: Smart Monitoring Water Quality through IoT-Enabled Sensors in RAS — Violitta Yesmaya, Jun-Xian Teng, et al. · Procedia Computer Science (2025) | TGRS Research Map | TGRS