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Research Article | Open Access |

IoT based Smart Water Quality Prediction for Biofloc Aquaculture

Author 1: Md. Mamunur Rashid Author 2: Al-Akhir Nayan Author 3: Sabrina Afrin Simi Author 4: Joyeta Saha Author 5: Md. Obaidur Rahman Author 6: Muhammad Golam Kibria
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 12, No. 6 · Published 2021 · Cited by 54

DOI: 10.14569/IJACSA.2021.0120608

Abstract

Traditional fish farming faces several challenges, including water pollution, temperature imbalance, feed, space, cost, etc. Biofloc technology in aquaculture transforms the manual into an advanced system that allows the reuse of unused feed by converting them into microbial protein. The objective of the research is to propose an IoT-based solution to aquaculture that increases efficiency and productivity. The article presented a system that collects data using sensors, analyzes them using a machine learning model, generates decisions with the help of Artificial Intelligence (AI), and sends notifications to the user. The proposed system has been implemented and tested to validate and achieve a satisfactory result.

Keywords

How to Cite this Article

Rashid, M. M., Nayan, A., Simi, S. A., Saha, J., Rahman, M. O., & Kibria, M. G. (2021). IoT based Smart Water Quality Prediction for Biofloc Aquaculture. International Journal of Advanced Computer Science and Applications, 12(6). https://doi.org/10.14569/IJACSA.2021.0120608

Rashid, Md. Mamunur, et al.. "IoT based Smart Water Quality Prediction for Biofloc Aquaculture." International Journal of Advanced Computer Science and Applications, vol. 12, no. 6, 2021, https://doi.org/10.14569/IJACSA.2021.0120608.

@article{Rashid2021,
  title     = {IoT based Smart Water Quality Prediction for Biofloc Aquaculture},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {6},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Md. Mamunur Rashid and Al-Akhir Nayan and Sabrina Afrin Simi and Joyeta Saha and Md. Obaidur Rahman and Muhammad Golam Kibria},
  doi       = {10.14569/IJACSA.2021.0120608},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120608}
}

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