Fuzzy logic-based adaptive aquaculture water monitoring system based on instantaneous limnological parameters

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Article

Source Title

Journal of Advanced Computational Intelligence and Intelligent Informatics

Volume

26

Issue

6

First Page

937

Last Page

943

Publication Date

2022

Abstract

Water quality is crucial for maintaining a sustainable living environment in aquaculture. Limnological pa- rameters affects the fish physiology, growth rate, and feed efficiency and may lead to high mortality rate un- der extreme conditions. The development of an adap- tive aquaculture monitoring system for water qual- ity using fuzzy logic will address this problem. Using Mamdani-type fuzzy inferences system (FIS) model, the input limnological parameters such as pH, tem- perature, total dissolved solids, and dissolved oxygen levels were transformed to four output states: excel- lent, good, poor, and toxic, for the prediction of water quality. For the simulation and evaluation of the de- veloped FIS, MATLAB Simulink was used. Results of this study can be integrated with a feedback system for appropriate treatments including filtering, aera- tion, and water flushing to maintain safe environment for Nile tilapia.

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Digitial Object Identifier (DOI)

10.20965/jaciii.2022.p0937

Disciplines

Environmental Engineering

Keywords

Aquaculture; Fuzzy systems; Limnology

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