Development of an Internet of Things-Based Water Quality Monitoring System for Shrimp Ponds Utilizing Mappi32

Indonesia's vast waters make its aquatic resources abundant, with one of the most valuable resources being Vannamei shrimp. Technology-based shrimp farming is an essential method for utilizing this resource. Maintaining optimal water quality parameters is necessary for successful shrimp farming, as it affects shrimp breeding. Ideal conditions for shrimp breeding include a temperature range of 26-32°C, salinity of 30-35 ppt, pH of 7.6-8.3, turbidity of 11-24 NTU, and oxygen levels of more than 4 mg/L. This research integrates sensors for real-time shrimp pond water quality monitoring using Internet of Things (IoT) technology, with sensors calibrated for error rate and accuracy. The error rates of the sensor testing process are TDS sensor 5.39%, temperature sensor 0.14%, pH sensor 2.85%, turbidity sensor 5.14%, and DO sensor 8.84%. This research successfully monitored the water quality of shrimp ponds in real-time through the Node-Red dashboard with the MQTT IoT protocol and an average latency of 593.3 ms. Over ten days, the average water quality parameters were as follows: in the morning salinity 31.86 ppt, temperature 27.13°C, pH 7.66, turbidity 17.24 NTU, and dissolved oxygen 5.22 mg/L; in the afternoon salinity 31.69 ppt, temperature 27.41°C, pH 7.84, turbidity 17.24 NTU, and dissolved oxygen 5.54 mg/L; and at night salinity 31.90 ppt, temperature 27.35°C, pH 7.78, turbidity 17.21 NTU, and dissolved oxygen 5.36 mg/L. Further research is needed to implement the Fuzzy Logic method to determine the optimal status of shrimp pond water and evaluate the effectiveness of the process on the control system.

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Publication Details

Journal
International Journal on Advanced Science Engineering and Information Technology
Published
2025-04-25
DOI
https://doi.org/10.18517/ijaseit.15.2.20339
Citations
1
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.82
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article

Development of an Internet of Things-Based Water Quality Monitoring System for Shrimp Ponds Utilizing Mappi32

Sri Ratna Sulistiyanti, Herlinawati Herlinawati, Bambang Hendrawan, Muhammad Ifan Saputra et al.
1 citations
International Journal on Advanced Science Engineering and Information Technology
Water Quality Monitoring Technologies
0.82
article

Development of an Internet of Things-Based Water Quality Monitoring System for Shrimp Ponds Utilizing Mappi32

Sri Ratna Sulistiyanti, Herlinawati Herlinawati, Bambang Hendrawan, Muhammad Ifan Saputra, Afri Yudamson
article en
1 citations

Abstract

Indonesia's vast waters make its aquatic resources abundant, with one of the most valuable resources being Vannamei shrimp. Technology-based shrimp farming is an essential method for utilizing this resource. Maintaining optimal water quality parameters is necessary for successful shrimp farming, as it affects shrimp breeding. Ideal conditions for shrimp breeding include a temperature range of 26-32°C, salinity of 30-35 ppt, pH of 7.6-8.3, turbidity of 11-24 NTU, and oxygen levels of more than 4 mg/L. This research integrates sensors for real-time shrimp pond water quality monitoring using Internet of Things (IoT) technology, with sensors calibrated for error rate and accuracy. The error rates of the sensor testing process are TDS sensor 5.39%, temperature sensor 0.14%, pH sensor 2.85%, turbidity sensor 5.14%, and DO sensor 8.84%. This research successfully monitored the water quality of shrimp ponds in real-time through the Node-Red dashboard with the MQTT IoT protocol and an average latency of 593.3 ms. Over ten days, the average water quality parameters were as follows: in the morning salinity 31.86 ppt, temperature 27.13°C, pH 7.66, turbidity 17.24 NTU, and dissolved oxygen 5.22 mg/L; in the afternoon salinity 31.69 ppt, temperature 27.41°C, pH 7.84, turbidity 17.24 NTU, and dissolved oxygen 5.54 mg/L; and at night salinity 31.90 ppt, temperature 27.35°C, pH 7.78, turbidity 17.21 NTU, and dissolved oxygen 5.36 mg/L. Further research is needed to implement the Fuzzy Logic method to determine the optimal status of shrimp pond water and evaluate the effectiveness of the process on the control system.

International Journal on Advanced Science Engineering and Information TechnologyVol. 15(2)
Lampung University (ID)
Openalex Percentile: Top 27%
Water Quality Monitoring Technologies
0.82
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