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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Murizah Kassim
Universiti Teknologi MARA
Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

 1 
Adaptive photovoltaic solar module based on internet of things and web-based monitoring system Murizah Kassim; Fadila Lazim
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp924-935

Abstract

This paper presents an intelligent of single axis automatic adaptive photovoltaic solar module. A static solar panel has an issue of efficiency on shading effects, irradiance of sunlight absorbed, and less power generates. This aims to design an effective algorithm tracking system and a prototype automatic adaptive solar photovoltaic (PV) module connected through internet of things (IoT). The system has successfully designated on solving efficiency optimization. A tracking system by using active method orientation and allows more power and energy are captured. The solar rotation angle facing aligned to the light-dependent resistor (LDR) voltage captured and high solar panel voltage measured by using Arduino microcontroller. Real-time data is collected from the dynamic solar panel, published on Node-Red webpage, and running interactive via android device. The system has significantly reduced time. Data captured by the solar panel then analyzed based on irradiance, voltage, current, power generated and efficiency. Successful results present a live data analytic platform with active tracking system that achieved larger power generated and efficiency of solar panel compared to a fixed mounted array. This research is significant that can help the user to monitor parameters collected by the solar panel thus able to increase 51.82% efficiency of the PV module.
A review on orchestration distributed systems for IoT smart services in fog computing Nor Syazwani Mohd Pakhrudin; Murizah Kassim; Azlina Idris
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1812-1822

Abstract

This paper provides a review of orchestration distributed systems for IoT smart services in fog computing. The cloud infrastructure alone cannot handle the flow of information with the abundance of data, devices and interactions. Thus, fog computing becomes a new paradigm to overcome the problem. One of the first challenges was to build the orchestration systems to activate the clouds and to execute tasks throughout the whole system that has to be considered to the situation in the large scale of geographical distance, heterogeneity and low latency to support the limitation of cloud computing. Some problems exist for orchestration distributed in fog computing are to fulfil with high reliability and low-delay requirements in the IoT applications system and to form a larger computer network like a fog network, at different geographic sites. This paper reviewed approximately 68 articles on orchestration distributed system for fog computing. The result shows the orchestration distribute system and some of the evaluation criteria for fog computing that have been compared in terms of Borg, Kubernetes, Swarm, Mesos, Aurora, heterogeneity, QoS management, scalability, mobility, federation, and interoperability. The significance of this study is to support the researcher in developing orchestration distributed systems for IoT smart services in fog computing focus on IR4.0 national agenda
A review on predictive maintenance technique for nuclear reactor cooling system using machine learning and augmented reality Ahmad Azhari Mohamad Nor; Murizah Kassim; Mohd Sabri Minhat; Norsuzila Ya'acob
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp6602-6613

Abstract

Reactor TRIGA PUSPATI (RTP) is the only research nuclear reactor in Malaysia. Maintenance of RTP is crucial which affects its safety and reliability. Currently, RTP maintenance strategies used corrective and preventative which involved many sensors and equipment conditions. The existing preventive maintenance method takes a longer time to complete the entire system’s maintenance inspection. This study has investigated new predictive maintenance techniques for developing RTP predictive maintenance for primary cooling systems using machine learning (ML) and augmented reality (AR). Fifty papers from recent referred publications in the nuclear areas were reviewed and compared. Detailed comparison of ML techniques, parameters involved in the coolant system and AR design techniques were done. Multiclass support vector machines (SVMs), artificial neural network (ANN), long short-term memory (LSTM), feed forward back propagation (FFBP), graph neural networks-feed forward back propagation (GNN-FFBP) and ANN were used for the machine learning techniques for the nuclear reactor. Temperature, water flow, and water pressure were crucial parameters used in monitoring a nuclear reactor. Image marker-based techniques were mainly used by smart glass view and handheld devices. A switch knob with handle switch, pipe valve and machine feature were used for object detection in AR markerless technique. This study is significant and found seven recent papers closely related to the development of predictive maintenance for a research nuclear reactor in Malaysia.
Linear regression and R-squared correlation analysis on major nuclear online plant cooling system Ahmad Azhari Mohamad Nor; Mohd Sabri Minhat; Norsuzila Ya’acob; Murizah Kassim
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp3998-4008

Abstract

The primary cooling system is an integral part of a nuclear reactor that maintains reactor operational safety. It is essential to investigate the effects of the cooling system parameter before implementing predictive maintenance techniques in the reactor monitoring system. This paper presents a linear regression and R-squared correlation analysis of the nuclear plant cooling system parameter in the TRIGA PUSPATI Reactor in Malaysia. This research examines the primary cooling system's temperature, conductivity, and flow rate in maintaining the nuclear reactor. Data collection on the primary coolant system has been analyzed, and correlation analysis has been derived using linear regression and R-squared analysis. The result displays the correlation matrix for all sensors in the primary cooling system. The R-squared value for TT5 versus TT2 is 89%, TT5 versus TT3 is 94%, and TT5 against TT4 is 66% which shows an excellent correlation to the linear regression. However, the conductivity sensor CT1 does not correlate with other sensors in the system. The flow rate sensor FT1 positively correlates with the temperature sensor but does not correlate with the conductivity sensor. This finding can help to better develop the predictive maintenance strategy for the reactor monitoring program.
Co-Authors Adiba Abd Ghafar Afdallyna Harun Ahmad Azhari Mohamad Nor Ahmad Syahir Arif Mohd Zaid Ahmad Zaki Abu Bakar Amirun Murtaza Abd Jalil Aziati Husna Awang Azita Laily Yusof Azlina Idris Cik Ku Haroswati Binti Che Ku Yahaya Cik Ku Haroswati Che Ku Yahaya Cik Ku Haroswati Che Ku Yahya Fadila Lazim Firdaus Hashim Hamizan Suhaimi Hasnorhafiza Husni Ismail Musirin Maisarah Abdul Rahman Mohamad Fazrul bin Rusdi Mohammad Saffri Mazalan Mohd Sabri Minhat Muhammad Fauzan Ayob Nor Sajidah Ab Ghani Nor Syazwani Mohd Pakhrudin Noraisyah Tajudin Norsuzila Ya'acob Norsuzila Yaa’cob Norsuzila Ya’acob Nuzli Mohamad Anas Roslina Mohamad Ruhani Ab Rahman Saiful Izwan Suliman Shahrani Shahbudin Syed Farid Syed Adnan Yuslinda Wati Mohamad Yusof Zaki Firdaus Mohmad