Improving fish feeding system in aquaponic performance /
Nur Mawaddah Alia Binti Alias,
Improving fish feeding system in aquaponic performance / Nur Mawaddah Alia Binti Alias - x, 49 pages : illustrations ;
Faculty of Chemical and Process Engineering Technology
Final Year Report (Bachelor of Chemical Engineering Technology) -- Universiti Malaysia Pahang Al-Sultan Abdullah - 2025
Include bibliographical reference
This study focuses on enhancing the performance and productivity of an aquaponic system through the redesign of the fish feeder and the implementation of automated monitoring and control. An aquaponic unit was assembled, integrating aquaculture (fish farming) and hydroponics (soil-less plant cultivation) components. This allows for a symbiotic environment whereby fish waste provides nutrients for the plants, and the plants help filter the water for the fish. However, inconsistent dispensing of fish feed from the existing feeder led to suboptimal conditions. To address this, a new fish feeder was digitally modelled using AutoCAD design software and then fabricated using 3D printing technology. The customized feeder allows for calibrated, timely, and reliable feed amounts to promote healthy fish growth. Furthermore, sensors were installed to monitor critical system parameters including pH and turbidity. The real-time sensor data is fed to an Arduino microcontroller which adjusts conditions accordingly to maintain equilibrium. For example, pH outside optimal ranges for either fish or plants triggers the automated system to dose acid or base until reaching the desired pH. A trial run highlighted fluctuations in turbidity and pH, indicating instability. The redesign of the poorly functioning feeder along with automated monitoring and control significantly improved system stability. Output in terms of fish biomass and plant yield is anticipated to increase through these upgrades. There remains ample potential to build on this foundation using techniques such as machine learning algorithms to analyze trends in sensor data and initiate condition adjustments. Multi-cycle testing over extended time periods will help maximize aquaponic productivity and viability as an innovative sustainable food production system.
THE0010519 (Local)
Faculty of Chemical and Process Engineering Technology--Dissertations
Universities and colleges--Dissertations
Theses--Dissertations
Improving fish feeding system in aquaponic performance / Nur Mawaddah Alia Binti Alias - x, 49 pages : illustrations ;
Faculty of Chemical and Process Engineering Technology
Final Year Report (Bachelor of Chemical Engineering Technology) -- Universiti Malaysia Pahang Al-Sultan Abdullah - 2025
Include bibliographical reference
This study focuses on enhancing the performance and productivity of an aquaponic system through the redesign of the fish feeder and the implementation of automated monitoring and control. An aquaponic unit was assembled, integrating aquaculture (fish farming) and hydroponics (soil-less plant cultivation) components. This allows for a symbiotic environment whereby fish waste provides nutrients for the plants, and the plants help filter the water for the fish. However, inconsistent dispensing of fish feed from the existing feeder led to suboptimal conditions. To address this, a new fish feeder was digitally modelled using AutoCAD design software and then fabricated using 3D printing technology. The customized feeder allows for calibrated, timely, and reliable feed amounts to promote healthy fish growth. Furthermore, sensors were installed to monitor critical system parameters including pH and turbidity. The real-time sensor data is fed to an Arduino microcontroller which adjusts conditions accordingly to maintain equilibrium. For example, pH outside optimal ranges for either fish or plants triggers the automated system to dose acid or base until reaching the desired pH. A trial run highlighted fluctuations in turbidity and pH, indicating instability. The redesign of the poorly functioning feeder along with automated monitoring and control significantly improved system stability. Output in terms of fish biomass and plant yield is anticipated to increase through these upgrades. There remains ample potential to build on this foundation using techniques such as machine learning algorithms to analyze trends in sensor data and initiate condition adjustments. Multi-cycle testing over extended time periods will help maximize aquaponic productivity and viability as an innovative sustainable food production system.
THE0010519 (Local)
Faculty of Chemical and Process Engineering Technology--Dissertations
Universities and colleges--Dissertations
Theses--Dissertations