Monitoring of Water Quality in Aquaculture Using IoT

Authors

  • C. Santhanakrishnan Department of CSE, SRMIST, Chennai, India Author
  • C. Mukesh Reddy Department of CSE, SRMIST, Chennai, India Author
  • C. Mukesh Reddy Department of CSE, SRMIST, Chennai, India Author
  • S. Dinesh Revanth Department of CSE, SRMIST, Chennai, India Author

DOI:

https://doi.org/10.61841/nchj0y54

Keywords:

Monitoring, Ecological modernization, Fish farming, detectors, PH sensor

Abstract

Water is indeed a critical aspect of daily existence. Owing to the ecological crisis, water protection and recycling are essential to human life. In recent years, there has been a tremendous need for user-based development projects that could be quickly built through Internet of Things (IoT) technology. In this paper, we suggest a water monitoring device centered on IoT that monitors water levels and PH rates in real time. Our project is based on the principle that the water quality degree may be a very critical factor.This includes of a temperature sensor, a turbidity sensor, a pH sensor and a water level sensor which have been constantly tracked and a standard level is set. When the measurements go above the fixed value then the automated monitoring is carried out, i.e. the temperature is regulated by coolant engine, the filter motor is being used for turbidity, the water motor is used for the water pressure. Throughout this device, the detectors are linked to the IoT portal and are linked to the central server. The cloud server manages the information and the values should be reflected in the Smartphone application.

 

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References

1. T. Abinaya, J. Ishwarya, and M. Maheswari, “A Novel Methodology for Monitoring and Controlling of Water Quality in Aquaculture using Internet of Things (IoT),” in 2019 International Conference on Computer Communication and Informatics, ICCCI 2019, 2019, doi: 10.1109/ICCCI.2019.8821988.

2. Z. Zhen, L. Wang, and Y. Zhang, “Aquaculture information recommendation based on collaborative filtering algorithm and web logs,” NongyeGongchengXuebao/Transactions Chinese Soc. Agric. Eng., 2017, doi: 10.11975/j.issn.1002-6819.2017.z1.039.

3. P. Gopi Krishna, P. Harish, K. Krishna Veni, G. Sai Kumar, and J. Raja sekhar, “Design and development of remote location water quality monitoring system using iot,” Int. J. Recent Technol. Eng., 2019.

4. S. Abraham, A. Shahbazian, K. Dao, H. Tran, and P. Thompson, “An Internet of Things (IoT)-based aquaponics facility,” 2017, doi: 10.1109/ghtc.2017.8239339.

5. F. L. Valienteet al., “Internet of things (IOT)-based mobile application for monitoring of automated aquaponics system,” in 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2018, 2019, doi: 10.1109/HNICEM.2018.8666439.

6. S. Saha, R. H. Rajib, and S. Kabir, “IoT Based Automated Fish Farm Aquaculture Monitoring System,” in 2018 International Conference on Innovations in Science, Engineering and Technology, ICISET 2018, 2018, doi: 10.1109/ICISET.2018.8745543.

7. M. Manju, V. Karthik, S. Hariharan, and B. Sreekar, “Real time monitoring of the environmental parameters of an aquaponic system based on internet of things,” in ICONSTEM 2017 - Proceedings: 3rd IEEE International Conference on Science Technology, Engineering and Management, 2017, doi: 10.1109/ICONSTEM.2017.8261342.

8. J. Ruanet al., “A Life Cycle Framework of Green IoT-Based Agriculture and Its Finance, Operation, and Management Issues,” IEEE Commun. Mag., 2019, doi: 10.1109/MCOM.2019.1800332.

9. K. R. S. R. Raju and G. H. K. Varma, “Knowledge based real time monitoring system for aquaculture Using IoT,” in Proceedings - 7th IEEE International Advanced Computing Conference, IACC 2017, 2017, doi: 10.1109/IACC.2017.0075.

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Published

31.10.2020

How to Cite

Santhanakrishnan, C., Reddy, C. M., Reddy, C. M., & Revanth, S. D. (2020). Monitoring of Water Quality in Aquaculture Using IoT. International Journal of Psychosocial Rehabilitation, 24(8), 2417-2423. https://doi.org/10.61841/nchj0y54