Enhanced analysis of photocurrent from photo sensor in food industry
Ideally, a sensor designed for the food industry should be equipped with a fast, precise, and reliable system to detect the physical properties of a substrate without causing direct or indirect damage. However, current photosensors are often very complex, as they focus on investigating the molec...
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Online Access: | http://irep.iium.edu.my/116025/7/116025_%20Enhanced%20analysis%20of%20photocurrent.pdf http://irep.iium.edu.my/116025/8/116025_%20Enhanced%20analysis%20of%20photocurrent_Scopus.pdf http://irep.iium.edu.my/116025/ https://ieeexplore.ieee.org/document/10652345 https://doi.org/10.1109/ICOM61675.2024.10652345 |
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my.iium.irep.1160252024-11-22T07:41:14Z http://irep.iium.edu.my/116025/ Enhanced analysis of photocurrent from photo sensor in food industry Mohd Yusoff, Marmeezee Alias, Mohd. Fahmi Hashim, Muhammad Adham Muzakki Mohamed, Ruziana Malek, Mohd Firdaus Mohammad Rosbi, Mohd Sofian Ismail, Ahmad Syakirin Kamarzaman, Azlin Haezrina TK452 Electric apparatus and materials. Electric circuits. Electric networks Ideally, a sensor designed for the food industry should be equipped with a fast, precise, and reliable system to detect the physical properties of a substrate without causing direct or indirect damage. However, current photosensors are often very complex, as they focus on investigating the molecular composition of the substrate, which takes a long time to yield results. Additionally, these systems are typically large and intricate. Therefore, this project focuses on developing a photosensor based on a photoelectrochemical structure that can detect the quality of the substrate, is easy to assemble, and provides rapid results. This project used stingless bee honey (Heterotrigona itama) as the substrate. Five different concentrations of stingless bee honey were tested by diluting the honey with specific amounts of distilled water. The photosensor employed in this project is Titanium Dioxide Nanorod Arrays (TNAs), chosen for their unique physical and chemical properties when exposed to UV light. The distance between the UV light source and the photosensor was varied to ensure reliable and valid experimental results. Furthermore, a fuzzy logic model was developed using MATLAB to accurately predict the quality of the stingless bee honey. The results demonstrated that pure stingless bee honey generated very low voltage compared to other concentrations. The distance between the UV light source and the TNAs was measured up to 31 cm, showing a decreasing voltage path with an error close to zero percent. The development of the fuzzy logic model from the experimental results proved to be reliable. IEEE 2024-09-04 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/116025/7/116025_%20Enhanced%20analysis%20of%20photocurrent.pdf application/pdf en http://irep.iium.edu.my/116025/8/116025_%20Enhanced%20analysis%20of%20photocurrent_Scopus.pdf Mohd Yusoff, Marmeezee and Alias, Mohd. Fahmi and Hashim, Muhammad Adham Muzakki and Mohamed, Ruziana and Malek, Mohd Firdaus and Mohammad Rosbi, Mohd Sofian and Ismail, Ahmad Syakirin and Kamarzaman, Azlin Haezrina (2024) Enhanced analysis of photocurrent from photo sensor in food industry. In: 9th International Conference on Mechatronics Engineering, ICOM 2024, 13-14 August 2024, Kuala Lumpur. https://ieeexplore.ieee.org/document/10652345 https://doi.org/10.1109/ICOM61675.2024.10652345 |
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TK452 Electric apparatus and materials. Electric circuits. Electric networks Mohd Yusoff, Marmeezee Alias, Mohd. Fahmi Hashim, Muhammad Adham Muzakki Mohamed, Ruziana Malek, Mohd Firdaus Mohammad Rosbi, Mohd Sofian Ismail, Ahmad Syakirin Kamarzaman, Azlin Haezrina Enhanced analysis of photocurrent from photo sensor in food industry |
description |
Ideally, a sensor designed for the food industry
should be equipped with a fast, precise, and reliable system to
detect the physical properties of a substrate without causing
direct or indirect damage. However, current photosensors are
often very complex, as they focus on investigating the molecular
composition of the substrate, which takes a long time to yield
results. Additionally, these systems are typically large and
intricate. Therefore, this project focuses on developing a
photosensor based on a photoelectrochemical structure that can
detect the quality of the substrate, is easy to assemble, and
provides rapid results. This project used stingless bee honey
(Heterotrigona itama) as the substrate. Five different
concentrations of stingless bee honey were tested by diluting the
honey with specific amounts of distilled water. The photosensor
employed in this project is Titanium Dioxide Nanorod Arrays
(TNAs), chosen for their unique physical and chemical
properties when exposed to UV light. The distance between the
UV light source and the photosensor was varied to ensure
reliable and valid experimental results. Furthermore, a fuzzy
logic model was developed using MATLAB to accurately
predict the quality of the stingless bee honey. The results
demonstrated that pure stingless bee honey generated very low
voltage compared to other concentrations. The distance
between the UV light source and the TNAs was measured up to
31 cm, showing a decreasing voltage path with an error close to
zero percent. The development of the fuzzy logic model from
the experimental results proved to be reliable. |
format |
Proceeding Paper |
author |
Mohd Yusoff, Marmeezee Alias, Mohd. Fahmi Hashim, Muhammad Adham Muzakki Mohamed, Ruziana Malek, Mohd Firdaus Mohammad Rosbi, Mohd Sofian Ismail, Ahmad Syakirin Kamarzaman, Azlin Haezrina |
author_facet |
Mohd Yusoff, Marmeezee Alias, Mohd. Fahmi Hashim, Muhammad Adham Muzakki Mohamed, Ruziana Malek, Mohd Firdaus Mohammad Rosbi, Mohd Sofian Ismail, Ahmad Syakirin Kamarzaman, Azlin Haezrina |
author_sort |
Mohd Yusoff, Marmeezee |
title |
Enhanced analysis of photocurrent from photo sensor in food industry |
title_short |
Enhanced analysis of photocurrent from photo sensor in food industry |
title_full |
Enhanced analysis of photocurrent from photo sensor in food industry |
title_fullStr |
Enhanced analysis of photocurrent from photo sensor in food industry |
title_full_unstemmed |
Enhanced analysis of photocurrent from photo sensor in food industry |
title_sort |
enhanced analysis of photocurrent from photo sensor in food industry |
publisher |
IEEE |
publishDate |
2024 |
url |
http://irep.iium.edu.my/116025/7/116025_%20Enhanced%20analysis%20of%20photocurrent.pdf http://irep.iium.edu.my/116025/8/116025_%20Enhanced%20analysis%20of%20photocurrent_Scopus.pdf http://irep.iium.edu.my/116025/ https://ieeexplore.ieee.org/document/10652345 https://doi.org/10.1109/ICOM61675.2024.10652345 |
_version_ |
1817841061199872000 |
score |
13.223943 |