Article

Development of a Low-Cost Solar Powered & Real-Time Water Quality Monitoring System for Malaysia Seawater Aquaculture: Application & Challenges

Authors:

Nur Aqilah Paskhal Rostam,

Nurul Hashimah Ahamed Hassain Malim,

Rosni AbdullahAuthors Info & Claims

ICCBDC '20: Proceedings of the 2020 4th International Conference on Cloud and Big Data Computing

Pages 86 - 91

https://doi.org/10.1145/3416921.3416928

Published: 24 September 2020 Publication History

Abstract

Harmful algal bloom (HAB) has been a long-term threat to the ecosystem as it pollutes water and reduces the safe water usage worldwide. Therefore, scientists and researchers dedicated tremendous time and efforts to prevent the growth of algal by monitoring and profiling the water quality index. However, provided that the expensive cost of the commercialised sensor, including the dynamic and causality of algae, complicated the process, this article discusses on the progress of a low-priced realtime monitoring system for water quality through the solar panel to perform preliminary studies on the water quality data. Profiling environmental readings is a crucial step in gaining an insight into the algal bloom growth. Furthermore, the real-time data collection from the system was continuously performed at the sea, leading to consistent data transfer to the server through a 3G network despite the remote monitoring. Notably, the two benefits of this system included the solution to the laborious process, which was based on manual sample collections. The second benefit was the database, which provided information on safe WQI for the fish farm and insight about algae growth, which could be used in the predictive modelling phase.

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Cited By

Sujatha MReza HRanganathan P(2024)A Conceptual Software Framework to Monitor Harmful Algal Blooms (HABs) in Lakes2024 IEEE 14th Annual Computing and Communication Workshop and Conference (CCWC)10.1109/CCWC60891.2024.10427825(0610-0619)Online publication date: 8-Jan-2024
https://doi.org/10.1109/CCWC60891.2024.10427825
Rostam NAhamed Hassain Malim NAzmee NFigueiredo ROsman MAbdullah R(2023)Harmful algal blooms (HAB) open issues: A review of ecological data challenges, factor analysis and prediction approaches using data-driven methodComputing and Artificial Intelligence10.59400/cai.v1i1.1001:1(100)Online publication date: 17-Nov-2023
https://doi.org/10.59400/cai.v1i1.100
de Camargo ESpanhol FSlongo Jda Silva MPazinato Jde Lima Lobo ACoutinho FPfrimer FLindino COyamada MMartins L(2023)Low-Cost Water Quality Sensors for IoT: A Systematic ReviewSensors10.3390/s2309442423:9(4424)Online publication date: 30-Apr-2023
https://doi.org/10.3390/s23094424
Show More Cited By

Index Terms

Development of a Low-Cost Solar Powered & Real-Time Water Quality Monitoring System for Malaysia Seawater Aquaculture: Application & Challenges
1. Computer systems organization
  1. Real-time systems
2. Hardware
  1. Emerging technologies

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cover image ACM Other conferences

ICCBDC '20: Proceedings of the 2020 4th International Conference on Cloud and Big Data Computing

August 2020

130 pages

ISBN:9781450375382

DOI:10.1145/3416921

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Brookes: Oxford Brookes University
Staffordshire University: Staffordshire University
University of Liverpool

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 September 2020

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TRANS DISCIPLINARY RESEARCH GRANT SCHEME (TRGS)

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ICCBDC '20

ICCBDC '20: 2020 4th International Conference on Cloud and Big Data Computing

August 26 - 28, 2020

Virtual, United Kingdom

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Cited By

Sujatha MReza HRanganathan P(2024)A Conceptual Software Framework to Monitor Harmful Algal Blooms (HABs) in Lakes2024 IEEE 14th Annual Computing and Communication Workshop and Conference (CCWC)10.1109/CCWC60891.2024.10427825(0610-0619)Online publication date: 8-Jan-2024
https://doi.org/10.1109/CCWC60891.2024.10427825
Rostam NAhamed Hassain Malim NAzmee NFigueiredo ROsman MAbdullah R(2023)Harmful algal blooms (HAB) open issues: A review of ecological data challenges, factor analysis and prediction approaches using data-driven methodComputing and Artificial Intelligence10.59400/cai.v1i1.1001:1(100)Online publication date: 17-Nov-2023
https://doi.org/10.59400/cai.v1i1.100
de Camargo ESpanhol FSlongo Jda Silva MPazinato Jde Lima Lobo ACoutinho FPfrimer FLindino COyamada MMartins L(2023)Low-Cost Water Quality Sensors for IoT: A Systematic ReviewSensors10.3390/s2309442423:9(4424)Online publication date: 30-Apr-2023
https://doi.org/10.3390/s23094424
Rostam NMalim NAbdullah RAhmad AOoi BChan D(2021)A Complete Proposed Framework for Coastal Water Quality Monitoring System With Algae Predictive ModelIEEE Access10.1109/ACCESS.2021.31020449(108249-108265)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3102044

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