Fuzzy Logic-Based Adaptive Aquaculture Water Monitoring System Based on Instantaneous Limnological Parameters

Water quality is crucial for maintaining a sustainable living environment in aquaculture. Limnological parameters affects the fish physiology, growth rate, and feed efficiency and may lead to high mortality rate under extreme conditions. The development of an adaptive aquaculture monitoring system f...

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Bibliographic Details
Published inJournal of advanced computational intelligence and intelligent informatics Vol. 26; no. 6; pp. 937 - 943
Main Authors Bautista, Mary Grace Ann C., Palconit, Maria Gemel B., Rosales, Marife A., II, Ronnie S. Concepcion, Bandala, Argel A., Dadios, Elmer P., Duarte, Bernardo
Format Journal Article
LanguageEnglish
Published Tokyo Fuji Technology Press Co. Ltd 20.11.2022
Subjects
Aeration
Aquaculture
Dissolved oxygen
Dissolved solids
Efficiency
Environmental impact
Fish
Fish production
Fisheries
Fishing
Fuzzy logic
Informatics
Internet of Things
Linguistics
Monitoring
Monitoring systems
Parameters
Physiology
Tilapia
Water purification
Water quality
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Summary:Water quality is crucial for maintaining a sustainable living environment in aquaculture. Limnological parameters affects the fish physiology, growth rate, and feed efficiency and may lead to high mortality rate under extreme conditions. The development of an adaptive aquaculture monitoring system for water quality using fuzzy logic will address this problem. Using Mamdani-type fuzzy inferences system (FIS) model, the input limnological parameters such as pH, temperature, total dissolved solids, and dissolved oxygen levels were transformed to four output states: excellent, good, poor, and toxic, for the prediction of water quality. For the simulation and evaluation of the developed FIS, MATLAB Simulink was used. Results of this study can be integrated with a feedback system for appropriate treatments including filtering, aeration, and water flushing to maintain safe environment for Nile tilapia.
ISSN:1343-0130
1883-8014
DOI:10.20965/jaciii.2022.p0937