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Fish disease detection system using fuzzy logic approach

With recent development of technologies, the scale of aquaculture have been growing steadily. One of the biggest problem with a large scale aquaculture operation is the monitoring and detection of disease. Large operation would need expert knowledge or longer time consumption. Traditional diagnosis...

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Main Author: Muhammad Amri Ambosakka
Format: Academic Exercise
Language:English
English
Published: 2022
Subjects:
Q1-390 Science (General)
SH171-179 Diseases and adverse factors
Online Access:https://eprints.ums.edu.my/id/eprint/33316/1/Fish%20Disease%20Detection%20System%20Using%20Fuzzy%20Logic%20Approach.24pages.pdf
https://eprints.ums.edu.my/id/eprint/33316/2/Fish%20Disease%20Detection%20System%20Using%20Fuzzy%20Logic%20Approach.pdf
https://eprints.ums.edu.my/id/eprint/33316/
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spelling my.ums.eprints.333162022-07-18T11:43:16Z https://eprints.ums.edu.my/id/eprint/33316/ Fish disease detection system using fuzzy logic approach Muhammad Amri Ambosakka Q1-390 Science (General) SH171-179 Diseases and adverse factors With recent development of technologies, the scale of aquaculture have been growing steadily. One of the biggest problem with a large scale aquaculture operation is the monitoring and detection of disease. Large operation would need expert knowledge or longer time consumption. Traditional diagnosis require human experts to diagnose the disease and this can be inaccurate. This research aims to solve this problem by providing a system to monitor the fishes remotely and to get a better accuracy of disease detection using the method of fuzzy logic. The system would help the operation to run more smoothly and reduce cost of operation for more profit. 4 common diseases were chosen for the testing of the system which was Dropsy, Fin Rot, Cotton Mouth, and Fish Tuberculosis. The system developed showed a result of 72.25% accuracy for the chosen diseases. 2022 Academic Exercise NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/33316/1/Fish%20Disease%20Detection%20System%20Using%20Fuzzy%20Logic%20Approach.24pages.pdf text en https://eprints.ums.edu.my/id/eprint/33316/2/Fish%20Disease%20Detection%20System%20Using%20Fuzzy%20Logic%20Approach.pdf Muhammad Amri Ambosakka (2022) Fish disease detection system using fuzzy logic approach. Universiti Malaysia Sabah. (Unpublished)
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic Q1-390 Science (General)
SH171-179 Diseases and adverse factors
spellingShingle Q1-390 Science (General)
SH171-179 Diseases and adverse factors
Muhammad Amri Ambosakka
Fish disease detection system using fuzzy logic approach
description With recent development of technologies, the scale of aquaculture have been growing steadily. One of the biggest problem with a large scale aquaculture operation is the monitoring and detection of disease. Large operation would need expert knowledge or longer time consumption. Traditional diagnosis require human experts to diagnose the disease and this can be inaccurate. This research aims to solve this problem by providing a system to monitor the fishes remotely and to get a better accuracy of disease detection using the method of fuzzy logic. The system would help the operation to run more smoothly and reduce cost of operation for more profit. 4 common diseases were chosen for the testing of the system which was Dropsy, Fin Rot, Cotton Mouth, and Fish Tuberculosis. The system developed showed a result of 72.25% accuracy for the chosen diseases.
format Academic Exercise
author Muhammad Amri Ambosakka
author_facet Muhammad Amri Ambosakka
author_sort Muhammad Amri Ambosakka
title Fish disease detection system using fuzzy logic approach
title_short Fish disease detection system using fuzzy logic approach
title_full Fish disease detection system using fuzzy logic approach
title_fullStr Fish disease detection system using fuzzy logic approach
title_full_unstemmed Fish disease detection system using fuzzy logic approach
title_sort fish disease detection system using fuzzy logic approach
publishDate 2022
url https://eprints.ums.edu.my/id/eprint/33316/1/Fish%20Disease%20Detection%20System%20Using%20Fuzzy%20Logic%20Approach.24pages.pdf
https://eprints.ums.edu.my/id/eprint/33316/2/Fish%20Disease%20Detection%20System%20Using%20Fuzzy%20Logic%20Approach.pdf
https://eprints.ums.edu.my/id/eprint/33316/
_version_ 1760231147514626048
score 13.211869

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