Engineering study on predictive functions of water quality in aquaponics systems

Singapore faces dire challenges on attaining food independence where 90% of her food supply is imported and is unable to tackle this challenge through conventional means since Singapore is a small nation with little land available for agriculture. Additionally, Singapore faces a shrinking working po...

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Main Author: Thia, Terance Jin Leon
Other Authors: Heng Kok Hui, John Gerard
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/166970
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1669702023-06-03T16:50:21Z Engineering study on predictive functions of water quality in aquaponics systems Thia, Terance Jin Leon Heng Kok Hui, John Gerard School of Mechanical and Aerospace Engineering mkhheng@ntu.edu.sg Engineering::Mechanical engineering Singapore faces dire challenges on attaining food independence where 90% of her food supply is imported and is unable to tackle this challenge through conventional means since Singapore is a small nation with little land available for agriculture. Additionally, Singapore faces a shrinking working population and ageing work force. The combination of aquaponics and agriculture automation could help address these challenges. Although there are some agriculture automation solutions on managing the health of crops available in the market, it is targeted towards medium to large scale aquaponics systems. As such, more can be done in the study of developing and/or researching of affordable solutions that provides the general public with personal aquaponics systems. This engineering study aims to develop an automated water quality management system that possesses the predictive function of determining a vital parameter without utilizing that parameter’s sensor. This study fulfills the aim by validation of sensor accuracy, data collection at an aquaponics farm, utilizing machine learning techniques, and integration of the data logging and predictive function to the developed water quality management system. The results of this study enabled the developed water quality system to be deployed with the advantage of cutting costs from sensor equipment and reduce man hours needed for managing water quality whilst maintaining an acceptable level of accuracy. Bachelor of Engineering (Mechanical Engineering) 2023-05-28T12:19:06Z 2023-05-28T12:19:06Z 2023 Final Year Project (FYP) Thia, T. J. L. (2023). Engineering study on predictive functions of water quality in aquaponics systems. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166970 https://hdl.handle.net/10356/166970 en A186 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
spellingShingle Engineering::Mechanical engineering
Thia, Terance Jin Leon
Engineering study on predictive functions of water quality in aquaponics systems
description Singapore faces dire challenges on attaining food independence where 90% of her food supply is imported and is unable to tackle this challenge through conventional means since Singapore is a small nation with little land available for agriculture. Additionally, Singapore faces a shrinking working population and ageing work force. The combination of aquaponics and agriculture automation could help address these challenges. Although there are some agriculture automation solutions on managing the health of crops available in the market, it is targeted towards medium to large scale aquaponics systems. As such, more can be done in the study of developing and/or researching of affordable solutions that provides the general public with personal aquaponics systems. This engineering study aims to develop an automated water quality management system that possesses the predictive function of determining a vital parameter without utilizing that parameter’s sensor. This study fulfills the aim by validation of sensor accuracy, data collection at an aquaponics farm, utilizing machine learning techniques, and integration of the data logging and predictive function to the developed water quality management system. The results of this study enabled the developed water quality system to be deployed with the advantage of cutting costs from sensor equipment and reduce man hours needed for managing water quality whilst maintaining an acceptable level of accuracy.
author2 Heng Kok Hui, John Gerard
author_facet Heng Kok Hui, John Gerard
Thia, Terance Jin Leon
format Final Year Project
author Thia, Terance Jin Leon
author_sort Thia, Terance Jin Leon
title Engineering study on predictive functions of water quality in aquaponics systems
title_short Engineering study on predictive functions of water quality in aquaponics systems
title_full Engineering study on predictive functions of water quality in aquaponics systems
title_fullStr Engineering study on predictive functions of water quality in aquaponics systems
title_full_unstemmed Engineering study on predictive functions of water quality in aquaponics systems
title_sort engineering study on predictive functions of water quality in aquaponics systems
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/166970
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