A comprehensive review of sensor-based and spectroscopy-based systems for monitoring water quality in freshwater aquaculture system

Ensuring precise water conditions is essential for the economic viability and preservation of aquatic resources in aquaculture, necessitating effective water quality monitoring systems. This research work investigates and reviews water quality monitoring systems for freshwater aquaculture, focusing...

Full description

Saved in:
Bibliographic Details
Main Authors: Ali, Ehtesham, Mohd Faizal, Jamlos, Raypah, Muna E., Mas Ira Syafila, Mohd Hilmi Tan, Bakhit, Abdelmoneim A., Muhammad Aqil Hafizzan, Nordin, Mohd Aminudin, Jamlos, Rashidah, Che Yob, Agus, Nugroho
Format: Article
Language:English
English
Published: Penerbit Akademia Baru 2024
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/40557/1/A%20Comprehensive%20Review%20of%20Sensor-based%20and%20Spectroscopy-based.pdf
http://umpir.ump.edu.my/id/eprint/40557/7/A%20Comprehensive%20Review%20of%20Sensor-Based%20and%20Spectroscopy-Based%20Systems.pdf
http://umpir.ump.edu.my/id/eprint/40557/
https://doi.org/10.37934/araset.56.1.248265
https://doi.org/10.37934/araset.56.1.248265
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.ump.umpir.40557
record_format eprints
spelling my.ump.umpir.405572024-10-14T00:21:40Z http://umpir.ump.edu.my/id/eprint/40557/ A comprehensive review of sensor-based and spectroscopy-based systems for monitoring water quality in freshwater aquaculture system Ali, Ehtesham Mohd Faizal, Jamlos Raypah, Muna E. Mas Ira Syafila, Mohd Hilmi Tan Bakhit, Abdelmoneim A. Muhammad Aqil Hafizzan, Nordin Mohd Aminudin, Jamlos Rashidah, Che Yob Agus, Nugroho TK Electrical engineering. Electronics Nuclear engineering Ensuring precise water conditions is essential for the economic viability and preservation of aquatic resources in aquaculture, necessitating effective water quality monitoring systems. This research work investigates and reviews water quality monitoring systems for freshwater aquaculture, focusing on electronic sensor-based and spectroscopy-based methods through a comparative analysis. The review categorizes and evaluates machine learning (ML)-based sensor and spectroscopy methods, emphasizing the performance of sensitive spectral bands linked to diverse water quality parameters. Furthermore, the research examines the efficiency and accuracy of water quality parameters in ML-based water quality monitoring systems for freshwater aquaculture. Comparative findings indicate that ML-based sensor methods exhibit superior quality, versatility, and performance, capitalizing on their ability to exploit unique spectral features. The discussion encompasses challenges and issues faced by ML-based water quality monitoring systems in freshwater aquaculture, providing insights into their future perspectives. This comprehensive investigation contributes valuable insights into the intricate relationship between sensing technologies, machine learning, and water quality monitoring in the context of freshwater aquaculture. It serves as a resource for stakeholders, researchers, and policymakers navigating the challenges of improving aquaculture practices while addressing environmental considerations. Penerbit Akademia Baru 2024-10-08 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40557/1/A%20Comprehensive%20Review%20of%20Sensor-based%20and%20Spectroscopy-based.pdf pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/40557/7/A%20Comprehensive%20Review%20of%20Sensor-Based%20and%20Spectroscopy-Based%20Systems.pdf Ali, Ehtesham and Mohd Faizal, Jamlos and Raypah, Muna E. and Mas Ira Syafila, Mohd Hilmi Tan and Bakhit, Abdelmoneim A. and Muhammad Aqil Hafizzan, Nordin and Mohd Aminudin, Jamlos and Rashidah, Che Yob and Agus, Nugroho (2024) A comprehensive review of sensor-based and spectroscopy-based systems for monitoring water quality in freshwater aquaculture system. Journal of Advanced Research in Applied Sciences and Engineering Technology, 56 (1). pp. 248-265. ISSN 2462-1943. (Published) https://doi.org/10.37934/araset.56.1.248265 https://doi.org/10.37934/araset.56.1.248265
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ali, Ehtesham
Mohd Faizal, Jamlos
Raypah, Muna E.
Mas Ira Syafila, Mohd Hilmi Tan
Bakhit, Abdelmoneim A.
Muhammad Aqil Hafizzan, Nordin
Mohd Aminudin, Jamlos
Rashidah, Che Yob
Agus, Nugroho
A comprehensive review of sensor-based and spectroscopy-based systems for monitoring water quality in freshwater aquaculture system
description Ensuring precise water conditions is essential for the economic viability and preservation of aquatic resources in aquaculture, necessitating effective water quality monitoring systems. This research work investigates and reviews water quality monitoring systems for freshwater aquaculture, focusing on electronic sensor-based and spectroscopy-based methods through a comparative analysis. The review categorizes and evaluates machine learning (ML)-based sensor and spectroscopy methods, emphasizing the performance of sensitive spectral bands linked to diverse water quality parameters. Furthermore, the research examines the efficiency and accuracy of water quality parameters in ML-based water quality monitoring systems for freshwater aquaculture. Comparative findings indicate that ML-based sensor methods exhibit superior quality, versatility, and performance, capitalizing on their ability to exploit unique spectral features. The discussion encompasses challenges and issues faced by ML-based water quality monitoring systems in freshwater aquaculture, providing insights into their future perspectives. This comprehensive investigation contributes valuable insights into the intricate relationship between sensing technologies, machine learning, and water quality monitoring in the context of freshwater aquaculture. It serves as a resource for stakeholders, researchers, and policymakers navigating the challenges of improving aquaculture practices while addressing environmental considerations.
format Article
author Ali, Ehtesham
Mohd Faizal, Jamlos
Raypah, Muna E.
Mas Ira Syafila, Mohd Hilmi Tan
Bakhit, Abdelmoneim A.
Muhammad Aqil Hafizzan, Nordin
Mohd Aminudin, Jamlos
Rashidah, Che Yob
Agus, Nugroho
author_facet Ali, Ehtesham
Mohd Faizal, Jamlos
Raypah, Muna E.
Mas Ira Syafila, Mohd Hilmi Tan
Bakhit, Abdelmoneim A.
Muhammad Aqil Hafizzan, Nordin
Mohd Aminudin, Jamlos
Rashidah, Che Yob
Agus, Nugroho
author_sort Ali, Ehtesham
title A comprehensive review of sensor-based and spectroscopy-based systems for monitoring water quality in freshwater aquaculture system
title_short A comprehensive review of sensor-based and spectroscopy-based systems for monitoring water quality in freshwater aquaculture system
title_full A comprehensive review of sensor-based and spectroscopy-based systems for monitoring water quality in freshwater aquaculture system
title_fullStr A comprehensive review of sensor-based and spectroscopy-based systems for monitoring water quality in freshwater aquaculture system
title_full_unstemmed A comprehensive review of sensor-based and spectroscopy-based systems for monitoring water quality in freshwater aquaculture system
title_sort comprehensive review of sensor-based and spectroscopy-based systems for monitoring water quality in freshwater aquaculture system
publisher Penerbit Akademia Baru
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/40557/1/A%20Comprehensive%20Review%20of%20Sensor-based%20and%20Spectroscopy-based.pdf
http://umpir.ump.edu.my/id/eprint/40557/7/A%20Comprehensive%20Review%20of%20Sensor-Based%20and%20Spectroscopy-Based%20Systems.pdf
http://umpir.ump.edu.my/id/eprint/40557/
https://doi.org/10.37934/araset.56.1.248265
https://doi.org/10.37934/araset.56.1.248265
_version_ 1822924677228527616
score 13.232414