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Smart IoT Biofloc Water Management System Using Decision Regression Tree

Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 437)


The conventional fishing industry has several difficulties: water contamination, temperature instability, nutrition, area, expense, etc. In fish farming, Biofloc technology turns traditional farming into a sophisticated infrastructure that enables the utilization of leftover food by turning it into bacterial biomass. The purpose of our study is to propose an intelligent IoT Biofloc system that improves efficiency and production. This article introduced a system that gathers data from sensors, stores data in the cloud, analyzes it using a machine learning model such as a decision regression tree model to predict the water condition, and provides real-time monitoring through an Android app. The proposed system achieved a satisfactory accuracy of 79% during the experiment.


  • Biofloc
  • IoT
  • Machine learning
  • Decision regression tree
  • Aquaculture

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Correspondence to A. S. M. Sharifuzzaman Sagar .

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Mozumder, S.A., Sharifuzzaman Sagar, A.S.M. (2022). Smart IoT Biofloc Water Management System Using Decision Regression Tree. In: Hossain, S., Hossain, M.S., Kaiser, M.S., Majumder, S.P., Ray, K. (eds) Proceedings of International Conference on Fourth Industrial Revolution and Beyond 2021 . Lecture Notes in Networks and Systems, vol 437. Springer, Singapore.

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