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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Nor Azlan Othman
Universiti Teknologi MARA
Electrical & Electronics Engineering

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Automated water quality monitoring system development via LabVIEW for aquaculture industry (Tilapia) in Malaysia Nor Azlan Othman; Nor Salwa Damanhuri; Mohamad Amirul Syafiq Mazalan; Sarah Addayani Shamsuddin; Mohd Hussaini Abbas; Belinda Chong Chiew Meng
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 2: November 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i2.pp805-812

Abstract

Maintaining the quality of the water quality is one of the important aspects that play a substantial effect on the aquaculture industry especially in the tilapia industry. The quality of the water needs to be continuously monitored as any deviation from the allowed critical parameters such as water temperature and potential of hydrogen (pH) can cause unwanted scenarios such as disease, stress, higher mortality rate and profit loss. Currently, the monitoring process adopted by most fish breeders is done manually by using a portable sensor. This approach is found to be very tedious, ineffective use of manpower and time consuming particularly for the large-scale aquaculture industry. Hence, this research focuses on developing a simple, low-cost automated water quality monitoring system for the tilapia industry via LabVIEW software. The developed system will be able to monitor the parameter in real-time continuously with the capability of record and analyze each reading in a more efficient way. A data acquisition (DAQ) of NI myRIO-1900 is used as an interface between sensors and a monitoring station equipped with LabVIEW. Additionally, the developed system is equipped with an alarm system to alert the user when any deviation of the parameters occurs. Result shows that the system has a small range of average relative error of 4.28% and 6.22% for temperature and pH level respectively as compare to the portable sensor. Note that the errors are down to the selection of sensors. Furthermore, the developed prototype of the monitoring system has advantages in terms of its flexibility in extending the system with more sensors and allows a longer period of data collection without human intervention. The system is also upgradable with the integration of a control element to control the parameter when the monitored parameter is exceeded the threshold value. Succinctly, the system offers lots of advantages to the aquaculture industries with further improvement leads to better performance.
Optical absorbance of RGB LEDs in pH measurement of colorimetric solution with phenol red reagent Mohd Rumaizan Maidan Dali; Aiman Shahmi Azam; Mohamad Faizal Abd Rahman; Khairul Azman Ahmad; Nor Azlan Othman; Mohd Hanapiah Abdullah; Ahmad Fairuz Omar
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1330-1337

Abstract

The use of red, green, and blue ( RGB ) light-emitting-diode ( LED ) is a new trend in monochromatic colorimetric sensing due to cost-effective implementation. However, the application of RGB LED in pH measurement depends on the performance of the LED colour towards the colorimetric solution of interest, hence, needs to be evaluated. This work evaluated the performance of RGB LED for pH measurement system based on colorimetric approach using phenol red as a reagent. The main objective was to identify the LED colour with the best performance in terms of signal response and a bsorbance behavior. In this work, LED and photodiode were used as optical components and NI USB DAQ with LabView as the processing software. Four samples with known pH values were prepared and tested to obtain the voltage and absorbance behavior of each LED colour. Among all, the blue LED with wavelength ranged between 450 - 495 nm showed the best sensing behavior based on its linearity and error. Both voltage response and absorbance produced linear correlation with R 2=0.883 and R 2=0.9803, respectively. The significant finding from this study is useful in selecting the best RGB LED that is suitable for colorimetric pH measurement with phenol red as its colorimetric reagent.
Performance evaluation of generative adversarial networks for generating mugshot images from text description Nur Nabilah Bahrum; Samsul Setumin; Nor Azlan Othman; Mohd Ikmal Fitri Maruzuki; Mohd Firdaus Abdullah; Adi Izhar Che Ani
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5895

Abstract

The process of identifying photos from a sketch has been explored by many researchers, and the performance of the identification process is almost perfect, particularly for viewed sketches. Suspect identification based on sketches is one of the applications in forensic science. To identify the suspect using these kinds of methods, a face sketch is required. Hence, the methods require skilled artists to sketch the suspect based on descriptions provided by eyewitnesses. However, the skills of these artists are different from one another, which results in different rendered sketches. Therefore, this work attempts to propose a new identification method based only on forensic face-written descriptions. To investigate the feasibility of the proposed method, this study has evaluated the performance of some text-to-photo generators on both viewed and forensic datasets using three different models of GAN which are SAGAN, DFGAN, and DCGAN. Then, the generated images are compared to the real photo contained within those datasets to evaluate how well the proposed method recognizes the faces. The results demonstrated that the recognition rate for the generated photos by the DCGAN models is better than the other two models which achieve a 38.3% recognition rate at rank-10 for mugshot identification.
Co-Authors Adi Izhar Che Ani Ahmad Fairuz Omar Aiman Shahmi Azam Belinda Chong Chiew Meng Khairul Azman Ahmad Mohamad Amirul Syafiq Mazalan Mohamad Faizal Abd Rahman Mohd Firdaus Abdullah Mohd Hanapiah Abdullah Mohd Hussaini Abbas Mohd Ikmal Fitri Maruzuki Mohd Rumaizan Maidan Dali Nor Salwa Damanhuri Nur Nabilah Bahrum Samsul Setumin Sarah Addayani Shamsuddin