Automatic Water Quality Monitoring System With Real-Time Data Type Based on Internet of Things (IOT) for Vannamei Shrimp Farming

Authors

  • Sobri Sobri Jakarta Technical University of Fisheries, Indonesia
  • Pungkas Prayitno Sutomo University Serang, Indonesia
  • Basino Basino Jakarta Technical University of Fisheries, Indonesia
  • Nurhayat Nurhayat Jakarta Technical University of Fisheries, Indonesia

DOI:

https://doi.org/10.53017/uje.64

Keywords:

Arduino Mega2560, NodeMCU esp8266, Monitoring System, Water quality

Abstract

Water quality is an important factor in supporting the success of vanname shrimp farming. The automatic water quality monitoring system is designed using two hardware, namely the DS18B290 temperature sensor to measure water temperature, the E-201 BNC pH meter kit sensor to measure water pH, and the TDS meter sensor. gravity Dfrobot to measure the salinity of the water, and the RED Turbidity MJKDZ sensor to measure the turbidity of the water, as the data sending hardware (transmitter). Arduino Mega2560 microcontroller, NodeMCU esp8266 as receiver and data processing hardware (reciver). The automatic water quality monitoring system is also designed using three software, namely Arduino IDE software as the main hardware program, ThingSpeak software as a database and MIT APP Inventor software as application development software. The test results for the level of accuracy and error of sensor measurements on water quality monitoring tools show that the sensor has a very good percentage of performance with the temperature sensor accuracy reaching 98.67%, the sensor reaching pH 99.35%, the salinity sensor reaching 99.28%. Meanwhile, the temperature sensor measurement error rate is only 1.32%, the pH sensor is only 0.64% and the salinity sensor is only 0.71%.

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Published

2021-09-26

How to Cite

Sobri, S., Prayitno, P., Basino, B., & Nurhayat, N. (2021). Automatic Water Quality Monitoring System With Real-Time Data Type Based on Internet of Things (IOT) for Vannamei Shrimp Farming. Urecol Journal. Part E: Engineering, 1(2), 52–63. https://doi.org/10.53017/uje.64

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