Journal of Electronic Voltage and Application
type: channel
description: The Journal of Electronic Voltage and Application (JEVA) is a peer reviewed, open-access journal which is aimed to help disseminate knowledge among the community. JEVA welcomes article submission for any original work and development in the field of electrical and electronics engineering that includes (but not limited to) Electrical Engineering, Power System, Communication System, Control and Robotics System, Computer Engineering, Networks System and Electronics Engineering. In addition, JEVA also publishes detailed case studies and review articles, as well as short communication and discussion. It is published twice a year (June and November) and there is no publication fee for the accepted manuscript. More Info
publisher: Penerbit UTHM
language: en
publication name: Journal of Electronic Voltage and Application
issn: 2716-6074
items: Developing a Smart Child Presence Detection in a Vehicles Using Thermal Camera
items: Evaluating Interoperability in EV Wireless Charging Systems: A Framework-Based Comparative Approach
items: Article Advances in Feature Extraction and Selection for Iris Recognition Systems: A Review
items: Comparison of Traditional PWM and Phase Disposition PWM for a 5-Level Cascaded H-Bridge (CHB) Inverter in Low-Voltage Applications
items: Performance Analysis of YOLOv8, YOLOv9, and YOLOv11 for Corn Leaf Disease Detection
items: Optimal Sizing and Location of Multi-Unit Photovoltaic System on Distribution Network Using Particle Swarm Optimization
items: Power Grid Synchronous Detection Based on Voltage and Frequency
items: Self-Sustaining Solar Panel Cleaning Solution with Integrated IoT Monitoring
items: Predictive Simulation of Wind Turbine Outputs at Mersing, Johor
items: Design and Implementation of a Smart Energy Management System (SEMS) for Food Truck DC Loads in Off-Grid Photovoltaic (OGPV)
items: Development of a Driver Drowsiness Detection System Using Infrared, Tilt and Heart Rate Sensors
items: High-Performance Bootstrapped Sample & Hold Circuit for ADCs: Achieving Low Power and Enhanced SNR/SNDR in 45nm CMOS Technology
items: Anomaly Detection Using Artificial Intelligence Methods: Support Vector Machine and Decision Tree Algorithms
items: Economic Viability Analysis of Electric Bikes over Conventional Bikes
items: Analysis of Total Harmonic Distortion in Inverter Systems: A Comparative Study of Square Wave, Phase Shift and Multilevel Inverters
items: Banana Leaf Disease Classification Using SqueezeNet, AlexNet and MobileNet
items: Design of an Off-Grid Hybrid Power Generation System for a Telecommunication Base-Transceiver Station: A Case Study of Cell Site at Oke-Imobi, Nigeria
items: Analyzing Voltage Stability in IEEE 57-Bus System Using Voltage Collapse Proximity Index (VCPI)
items: IoT-Enabled Bus Tracking System for Real-Time Campus Transportation
items: IoT-Based Automated Cabinet System for Drugs Storage and Accurate Retrieval for Operation Theater Application
items: A Smart Chair for Sitting Postures Monitoring and Seat Occupancy Detection
items: Simulation of Absorption Cross Section: A Preliminary Study of Infrared Absorption Spectroscopy for Sulfur Dioxide Gas Measurement
items: IoT-Based Smart Liquid Medicine Dispenser for Dysphagia Symptom Patients
items: Development of Epileptic Seizure Symptoms Detection Device
items: Solar-Powered Smart Bus Shelter in UTHM Campus
items: Indoor Location Sensing Using Multiple Wireless Standards
items: Bi- Level Optimization of Multi-Microgrids: A Review Considering Demand Response Aggregators
items: Sustainable Water Solutions: Solar- Driven Distillation and Real-Time Monitoring for Rural Community
items: Hardware Implementation of the Activation Layer and Mean Pooling Layer for the CNN Digit Recognition
items: Portable Environmental Monitoring System using IOT (PEMS)

Developing a Smart Child Presence Detection in a Vehicles Using Thermal Camera
type: item
description: Children left unattended in parked cars face severe risks due to rapidly rising cabin temperatures, often leading to heatstroke or fatalities. Even on moderately warm days, interiors can reach life-threatening levels within minutes, and despite awareness campaigns, these incidents continue, highlighting the urgent need for proactive detection systems.This project presents a smart child presence detection system for vehicles using thermal imaging and deep learning, designed on preventing fatalities caused by vehicular heatstroke. The system integrates the MLX90640 thermal camera with a Raspberry Pi 5 and leverages the YOLOv8s object detection model to identify human heat signatures in real time. Unlike conventional camera-based or multi-sensor solutions, this work introduces a lightweight, cost-effective approach that ensures reliable detection regardless of lighting conditions. A key novelty of this system lies in its fully embedded implementation, performing all processing locally on the Raspberry Pi to enable fast, autonomous operation without external infrastructure. The system is designed to trigger an alert when a human is detected in the vehicle cabin, activating a buzzer and sending a thermal image notification to the caregiver via a Telegram bot. A five-minute delay mechanism is included to prevent repeated alerts unless manually reset. The YOLOv8s model was trained on a custom thermal dataset and tested under varying distances, angles, and body positions to simulate realistic in-vehicle conditions. Comparative evaluation with a commercial infrared thermometer confirmed the MLX90640’s capability in detecting human heat signatures. The results demonstrate the feasibility and potential of combining thermal sensing with on-device AI for real-time child presence detection in vehicles.
subject: Articles
  topic: section
subject: human detection
  topic: keywords
subject: YOLO
  topic: keywords
subject: MLX90640
  topic: keywords
subject: TelegramBot
  topic: keywords
subject: Raspberry Pi
  topic: keywords
subject: AI
  topic: keywords
subject: Thermal heat Camera
  topic: keywords
subject: Thonny
  topic: keywords
creator: Mohamad Hasnan Mohd Ali
creator: Zuhairiah Zainal Abidin
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 18
ending page: 31

Evaluating Interoperability in EV Wireless Charging Systems: A Framework-Based Comparative Approach
type: item
description: Wireless Power Transfer (WPT) technology has emerged as a promising solution for convenient and safe Electric Vehicle (EV) charging. However, the lack of interoperability between wireless charging systems developed by different manufacturers due to the diversity of international standards such as SAE J2954, IEC 61980, and ISO 15118 poses significant barriers to large-scale adoption. This paper presents a comprehensive review of the current WPT standard and its technical specifications, and is followed by an analysis of interoperability challenges in EV charging systems. Based on these identified gaps, we propose a conceptual framework to evaluate technical interoperability across various WPT implementations. This framework certainly also considers key parameters such as frequency alignment, coil compatibility, power level, communication protocol, and safety features. The results of this study provide insights for developers, manufacturers, and regulators in aligning the WPT system to support EV charging infrastructure that can be operated in the future.
subject: Articles
  topic: section
subject: Wireless Power Transfer (WPT)
  topic: keywords
subject: Electric Vehicle (EV)
  topic: keywords
subject: interoperability
  topic: keywords
subject: SAE J2954
  topic: keywords
subject: IEC 61980
  topic: keywords
subject: ISO 15118
  topic: keywords
subject: standards comparison
  topic: keywords
subject: technical evaluation framework
  topic: keywords
subject: Energy and electricity management
  topic: disciplines
creator: Panji Narputro
creator: Anang Suryana
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 1
ending page: 17

Article Advances in Feature Extraction and Selection for Iris Recognition Systems: A Review
type: item
description: The growing demand for security and reliable authentication methods has positioned biometric recognition systems at the forefront of modern security infrastructure. Among various biometric modalities, including facial and fingerprint, iris recognition has emerged as the most accurate and reliable, due to its rich texture, stability over time, and resistance to ageing and surgical alteration. However, existing iris recognition systems are primarily optimized for frontal, high-quality images and often fail to accurately process angular or partially captured iris images. To overcome these issues, techniques such as feature extraction, segmentation, and normalization need to be improved. Feature selection is essential in dimensionality reduction, and when combined with feature extraction techniques, the process will improve both time complexity and accuracy. This review explores the advancements in iris recognition, focusing on feature extraction and selection techniques that are crucial for improving system accuracy and efficiency. This study offers a comprehensive overview of various feature extraction and selection techniques, serving as a valuable reference for researchers.
subject: Articles
  topic: section
subject: Biometric
  topic: keywords
subject: Feature Extraction
  topic: keywords
subject: Feature Selection
  topic: keywords
subject: iris recognition
  topic: keywords
creator: Muhammad Ghali Aliyu
creator: Sapiee Jamel
creator: Muktar Danlami
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 148
ending page: 165

Comparison of Traditional PWM and Phase Disposition PWM for a 5-Level Cascaded H-Bridge (CHB) Inverter in Low-Voltage Applications
type: item
description: Multilevel inverters play an important role in power systems as they provide better output waveform quality and help reduce harmonic distortion (THD). In this paper, a 5-level Cascaded H-Bridge (CHB) inverter is designed and tested using MATLAB Simulink. The inverter consists of two H-bridge cells, with each cell supplied by an equal DC voltage source. The 5-level configuration is chosen because it requires fewer switching devices compared to a 7-level inverter and is easier to implement, particularly for small low-voltage systems. Two modulation methods are used in this simulation. The first is Traditional PWM (TPWM), which employs one sine wave and one triangular carrier wave. The second is Phase Disposition PWM (PDPWM), where multiple triangular carriers are all in the same phase. Both PWM methods are tested under the same conditions, using a 50 Hz fundamental frequency to match the Malaysian power supply standard. To analyze the effect of filtering, the inverter is tested before and after applying a passive LC filter. Simulation results show that THD is reduced from 57.40% to 5.81% for TPWM, and from 27.38% to 1.83% for PDPWM after filtering. These results demonstrate that PDPWM is more effective when used with a passive filter. This work highlights the potential of PDPWM for applications in renewable energy systems, motor drives, and electric vehicles, and suggests opportunities for future exploration of advanced PWM strategies such as Modified PWM (MPWM) and AI-based modulation.
subject: Articles
  topic: section
subject: Multilevel inverter
  topic: keywords
subject: Traditional PWM (TPWM)
  topic: keywords
subject: Modified PWM (MPWM)
  topic: keywords
subject: Phase Disposition PWM (PDPWM)
  topic: keywords
subject: Total Harmonic Distortion (THD)
  topic: keywords
subject: MATLAB Simulink
  topic: keywords
subject: Cascaded H-Bridge
  topic: keywords
subject: Advanced Power Electronics
  topic: disciplines
creator: Mohd Khairy Hassan
creator: Ahmad Mazlan Ahmad Zaidi
creator: Brian Crisswill G Giserlerry
creator: Paran Jonly
creator: Asmarashid Ponniran
creator: Afarulrazi Abu Bakar
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 104
ending page: 112

Performance Analysis of YOLOv8, YOLOv9, and YOLOv11 for Corn Leaf Disease Detection
type: item
description: Corn is a crucial crop for agricultural yield and food security, yet it faces significant threats from various foliar diseases that can diminish both growth and quality. Conventional visual assessment techniques often require substantial labor and are susceptible to errors in diagnosis. This study introduces a Corn Leaf Disease Detection System that employs Convolutional Neural Networks (CNNs) and evaluates the performance of three models: YOLOv8, YOLOv9, and YOLOv11. The methodology involves capturing high-resolution images of corn leaves afflicted by diseases such as Northern Leaf Blight and Common Rust. These images undergo a pre-processing phase to enhance clarity and are standardized for input into the detection framework. CNN is employed for intricate classification tasks, while YOLOv11 is utilised for real-time disease detection. The dataset comprises 3,000 images, which are augmented to expand the training set to 6,000 samples. Among the evaluated models, YOLOv11 demonstrated superior performance, achieving an F1-score of 0.93, with precision at 0.94 and recall at 0.92 by epoch 100. These findings highlight the system's operational efficiency and robustness in effectively detecting corn leaf diseases.
subject: Articles
  topic: section
subject: Image Processing
  topic: keywords
subject: Precision Agriculture
  topic: keywords
subject: Corn Leaf Disease
  topic: keywords
subject: Deep Learning
  topic: keywords
subject: YOLOv8
  topic: keywords
subject: YOLOv9
  topic: keywords
subject: YOLOv11
  topic: keywords
subject: Convolutional Neural Netwrok (CNN)
  topic: keywords
creator: Shafieka Nadia Sabarudin
creator: Nik Shahidah Afifi Md Taujuddin
creator: Suhaila Sari
creator: Ahmad Raqib Ab Ghani
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 126
ending page: 139

Optimal Sizing and Location of Multi-Unit Photovoltaic System on Distribution Network Using Particle Swarm Optimization
type: item
description: This paper investigates the optimal sizing and location of multi-unit photovoltaic (PV) systems in a distribution network using Particle Swarm Optimization (PSO). The goal is to reduce power losses and improve voltage stability by installation PV as distributed generator (DG). The IEEE 33-bus and 69-bus radial distribution systems were used as test system. Power flow analysis was conducted using the Newton-Raphson method in MATLAB software. Simulation results revealed that integrating three PV units provided the best performance, reducing power losses by 65.52% and 69.16% for the IEEE 33-bus and 69-bus systems respectively. A scenario with a 20% increase in total load was also analyzed to simulate the impact of electric vehicle charging station (EVCS) to PV sizing and location. It found that, proper sizing and placement of PV integration can improve the network losses when EVCS connected to the distribution system.
subject: Articles
  topic: section
subject: Distributed Generation (DG)
  topic: keywords
subject: EV Charging Station
  topic: keywords
subject: Photovoltaic (PV)
  topic: keywords
subject: Particle Swarm Optimization (PSO)
  topic: keywords
subject: Power Loss Reduction
  topic: keywords
subject: Voltage Stability
  topic: keywords
creator: Mohamad Nor Akhmal Mohd Najib
creator: Mohd Noor Abdullah
creator: Khairul Rijal Wagiman
creator: Mochammad Junus
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 113
ending page: 125

Power Grid Synchronous Detection Based on Voltage and Frequency
type: item
description: The power grid system is a complex electrical network that supply electricity from power generation to consumers. Required the variation of voltage and frequency are maintained within the normative limits. The aim of this research is to design a circuit model that simulate a power grid synchronous system using Proteus 8.17 software. This research had designed and built a model that can detect grid condition based on voltage and frequency variation. Arduino UNO microcontroller had been used in this research to control the overall operation flow. The functionality of the model had been examined through software simulation testing. Six different conditions had been set to test the functionality of the model. The assigned conditions include Normal Voltage (between 207V and 253V), Under Voltage (<207V), Over Voltage (>253V), Normal Frequency (between 49.5Hz and 50.5Hz), Under Frequency (<49.5Hz) and Over Frequency (>50.5Hz). Overall, the developed model in simulation using Proteus 8.17 software had a accuracy when detecting grid based on over/under voltage and over/under frequency variation.
subject: Articles
  topic: section
subject: Power Grid
  topic: keywords
subject: Synchronous
  topic: keywords
subject: Proteus software
  topic: keywords
subject: Arduino UNO
  topic: keywords
subject: Microcontroller
  topic: keywords
subject: Variation
  topic: keywords
subject: Voltage
  topic: keywords
subject: Frequency
  topic: keywords
creator: Muhammad Aiman Adam Ahmad Khairi
creator: Suriana Salimin
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 95
ending page: 103

Self-Sustaining Solar Panel Cleaning Solution with Integrated IoT Monitoring
type: item
description: Deposition of dust on photovoltaic panels significantly reduces their power output efficiency, posing a major hindrance to optimal solar energy generation. In this article, the development of a self-sustaining solar panel cleaning system with an inbuilt Internet of Things (IoT) platform for real-time monitoring and control is reported. The system design suggested herein combines a wiper mechanism and a centrifugal air blower powered by a monocrystalline solar panel for effective removal of dust and debris. The cleaning cycle is made automatic using a dust sensor and real-time clock (RTC) module with an override facility through the Blynk IoT interface. Environmental and electrical parameters such as dust density, panel output voltage, current, and power are also monitored by the system. Results indicated a considerable power output increase after cleaning operations, validating the effectiveness and feasibility of the system as a cost-effective, environmentally friendly means of domestic solar panel cleaning.
subject: Articles
  topic: section
subject: solar pv claeaning
  topic: keywords
subject: IoT monitoring
  topic: keywords
subject: automated wiper
  topic: keywords
subject: dust sensor
  topic: keywords
subject: renewable energy
  topic: keywords
subject: smart maintenance
  topic: keywords
creator: Ahmad Baihaqie Yusoff Zaki
creator: Mohammad Faiz Liew Abdullah
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 85
ending page: 94

Predictive Simulation of Wind Turbine Outputs at Mersing, Johor
type: item
description: Wind power potential in tropical nations such as Malaysia is typically having low and fluctuating wind speeds, rendering traditional Horizontal Axis Wind Turbines (HAWTs) not as effective. This project solves the dilemma of power output calculation of Vertical Axis Wind Turbines (VAWTs) confidently, which are more appropriate for low-wind regions but for which there are no applicable tools of assessment. This study tries to develop a simulation model that calculates power output of a VAWT based on real environmental readings for example, wind speed, temperature, and relative humidity. Dynamic estimation of power output and air density were included in a working mathematical block model and performed using ideal wind power equation. Environmental readings measured from two Malaysian sites, Batu Pahat and Mersing, were employed in order to explore and test the model. Outputs shows that Mersing whose average wind speed met and exceeded that of turbine cut-in, held up maximum energy output of 34,930 Wh in February, in comparison to Batu Pahat which was likely to fall short of power delivery due to low wind speed. Simulation outcomes also concluded that temperature and humidity significantly influence air density, and hence, turbine efficiency. Lastly, aforesaid proposed model constitutes a certain tool in assessing VAWT viability on the basis of low-wind, high-humidity areas. It upholds early-stage planning, site selection, and early-stage feasibility determination because it provides credible simulations of wind energy output in compliance with changing tropical conditions.
subject: Articles
  topic: section
subject: Wind Turbine Power Output
  topic: keywords
subject: Vertical -Axis Wind Turbine
  topic: keywords
subject: Renewable Energy in Malaysia
  topic: keywords
creator: Muhammad Adam Asyraf Salleh
creator: Suriana Salimin
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 140
ending page: 147

Design and Implementation of a Smart Energy Management System (SEMS) for Food Truck DC Loads in Off-Grid Photovoltaic (OGPV)
type: item
description: Mobile food trucks need diesel generators or gasoline to produce power to operate essential appliances. This leads to increased fuel expenditures, emissions, and noise pollution, which are harms to the environment, as well as customers’ and employees' experience. To reduce these burdens, this project was to design and develop a Smart Energy Management System (SEMS) to replace the need for a diesel generator by integrating it with an Off-Grid Photovoltaic (OGPV) to power DC loads more efficiently. An energy demand analysis was conducted on four food trucks located in Kuala Lumpur; the data collected from the appliances was analyzed to create an Excel-based tool that allowed us to determine the optimal sizes of PV panels, batteries, and MPPT charge controllers that provided a two-day autonomy (for cloudy days). The tools were validated using the PVsyst software and the analysis showed an average load demand error of lower than 0.4% which validated the tool's effectiveness. A SEMS prototype with an ESP32 microcontroller was built that utilized voltage, current, light, and rain sensors, and the prototype was able to automate lighting control and monitor real-time data using an LCD display and Arduino IoT Cloud. Testing in the day, night, and rain proved the system's capacity to manage energy very efficiently along with reliable operations and the ability to adapt to variable environments. To summarize, the integrated SEMS-OGPV system provides a real-world user outcome as a practical, sustainable, and scalable energy solution for mobile food operations considering the accurate sizing, optimized efficiencies, and greater environmental considerations.
subject: Articles
  topic: section
subject: Smart Energy Management System
  topic: keywords
subject: Off-Grid Photovoltaic
  topic: keywords
subject: food truck
  topic: keywords
subject: DC loads
  topic: keywords
subject: Excel-based tool
  topic: keywords
subject: Arduino IoT Cloud
  topic: keywords
creator: Harith Aiman Suhaimi
creator: Suriana Salimin
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 73
ending page: 84

Development of a Driver Drowsiness Detection System Using Infrared, Tilt and Heart Rate Sensors
type: item
description: Driver drowsiness is a major contributor to road accidents, making early detection systems essential for enhancing vehicle safety. This paper presents the design and evaluation of a wearable drowsiness detection prototype integrating an infrared (IR) sensor for eye blink monitoring, an MPU6050 accelerometer for head tilt detection, and a MAX30100 sensor for heart rate and oxygen saturation measurement. Laboratory validation was first carried out using servo motors and oscilloscope readings to simulate eyelid movement and head tilts. The system was then tested in-vehicle under real driving conditions, where real-time monitoring of eye status, head posture, and heart rate was displayed on an LCD with buzzer and LED alerts. Results demonstrated reliable detection of prolonged eye closure, abnormal head tilts, and reduced heart rate, with an estimated overall accuracy of approximately 85%. These findings confirm that combining behavioral and physiological indicators enhances detection robustness compared to single-parameter systems. The prototype demonstrates a low-cost, portable, and non-intrusive solution for drowsiness detection, making it suitable for vehicles lacking advanced driver-assistance systems. Furthermore, the use of easily available components allows for wide applicability and integration into various vehicle types. Future research will focus on refining adaptive thresholds, conducting long-term driving trials, and applying machine learning techniques to further improve detection reliability.
subject: Articles
  topic: section
subject: Driver fatigue
  topic: keywords
subject: Vehicle safety
  topic: keywords
subject: Infrared sensors
  topic: keywords
subject: Head movement monitoring
  topic: keywords
subject: Heart rate sensor
  topic: keywords
subject: Wearable sensors
  topic: keywords
creator: Aida Farzana Mohd Faizal
creator: Rahmat Talib
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 32
ending page: 41

High-Performance Bootstrapped Sample & Hold Circuit for ADCs: Achieving Low Power and Enhanced SNR/SNDR in 45nm CMOS Technology
type: item
description: A sample and hold (S/H) system is commonly used alongside Analog to Digital Converters (ADCs) to accurately convert analog signals into digital form. This paper presents a low-power bootstrapped S/H circuit designed to improve signal-to-noise ratio (SNR), signal-to-noise and distortion ratio (SNDR), and power efficiency in both low and high-frequency applications. By charging the bootstrap capacitor through a connection between the transistor's source and body, the input range is increased, which lowers power consumption without affecting the SNDR. The proposed design, developed using the bootstrapped method, maintains the functionality of the sample and hold circuit while boosting the differential input signal amplitude to 300mV in 45nm CMOS technology. The design demonstrates minimal power consumption of 0.21, 0.027, and 0.23µW, while achieving higher SNR values of 72.43, 66.79, and 77.57dB at 50, 100, and 500MS/s, respectively. Additionally, the SNDR shows improved values of 52.47, 52.95, and 51.22dB at those same sampling rates. The proposed bootstrapped S/H circuit was simulated using LT Spice IV in 45nm CMOS technology.
subject: Articles
  topic: section
subject: Analog to Digital converter
  topic: keywords
subject: Sample and Hold
  topic: keywords
subject: Bootstrapped
  topic: keywords
subject: SNDR
  topic: keywords
subject: 45nm_HP CMOS technology
  topic: keywords
subject: Power Consumption
  topic: keywords
creator: Md Hasan Maruf
creator: Siful Islam Pranto
creator: Md. Shakib Ibne Ashrafi
creator: Sadi Mohammad Moin
creator: Mohi Uddin Ahmed
creator: Murad Kabir Nipun
creator: ASM Shihavuddin
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-06-27
publication date: 2025-06-27
starting page: 59
ending page: 69

Anomaly Detection Using Artificial Intelligence Methods: Support Vector Machine and Decision Tree Algorithms
type: item
description: For anyone using a network, safeguarding personal or sensitive information is a top priority. Anomaly detection plays a crucial role in spotting irregular patterns that could signal malicious behaviour and help to prevent data breaches, defend against cyberattacks, and ensure the integrity of network resources. Hence, this study explores how machine learning can be used to detect unusual or suspicious activity in network traffic, a key step in protecting systems from threats like Denial of Service (DoS) attacks, unauthorised access, and probing attempts. Using the improved NSL-KDD dataset, which builds on the original KDD Cup 1999 dataset, two popular algorithms: Decision Trees and Support Vector Machines (SVM) with a polynomial kernel were tested. The models were applied to classify network traffic as either normal or potentially harmful, helping assess their effectiveness in identifying anomalies and supporting stronger network security. The Decision Tree model demonstrated a remarkable accuracy of 99.7% with an F-score of 0.997, showcasing its robustness in detecting prevalent attack patterns with high precision. Conversely, the Polynomial Kernel SVM exhibited a slightly lower accuracy of 99.5% but demonstrated stronger generalisation across various classes, reflected by a macro average F-score of 0.72. This indicates its superior capability to handle diverse and complex anomalies. The findings highlighted that both models are highly effective for intrusion detection, with the Decision Tree excelling in overall accuracy and the SVM offering a more balanced performance across a range of attack types. This research contributes to the ongoing development of intrusion detection systems, providing valuable insights into the trade-offs between model complexity, computational efficiency, and detection accuracy in real-time network security contexts.
subject: Articles
  topic: section
subject: Anomaly detection
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Decision Tree
  topic: keywords
subject: Support Vector Machine
  topic: keywords
creator: Emmanuel Ubom
creator: Andikan E. Okoro
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 61
ending page: 72

Economic Viability Analysis of Electric Bikes over Conventional Bikes
type: item
description: In India, two-wheelers have taken over the transportation industry, with a large portion of the vehicles sold in the country and being used as a major means of transportation. The trend of sustainable transport in the world has made electric vehicles (EVs) an attractive alternative to internal combustion engine (ICE) vehicles, which can potentially save energy and minimize greenhouse gas emissions. Nevertheless, the lack of clarity in the total cost of ownership (TCO) is a barrier to EV adoption in India. The paper is a comparison of TCO of electric two-wheelers (E2Ws) and ICE bikes based on real-world models such as the Revolt RV400 and Honda CB Shine 125cc. The initial costs, running costs (electricity/fuel), and the cost of replacing the battery are calculated using a methodological cost framework, which is supported with the EV Calculator Pro application. The findings indicate that EV running costs (0.25-0.98/km) are 31-67 percent less than ICE costs (1.42-2.00/km), and the Revolt RV400 saves 67 percent compared to the Honda CB Shine. The costs of battery replacement (0.40-0.48/km) are also a major consideration. The paper finds that EVs can be cost-effective and is environmentally friendly and suggests that the policy measures, such as subsidies and charging networks, should be implemented to increase adoption.
subject: Articles
  topic: section
subject: electric two-wheelers,
  topic: keywords
subject: total cost of ownership
  topic: keywords
subject: internal combustion engine,
  topic: keywords
subject: battery replacement cost
  topic: keywords
subject: EV Calculator Pro
  topic: keywords
subject: sustainable transport
  topic: keywords
subject: India
  topic: keywords
creator: Praveen Kumar
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 53
ending page: 60

Analysis of Total Harmonic Distortion in Inverter Systems: A Comparative Study of Square Wave, Phase Shift and Multilevel Inverters
type: item
description: This study investigates the total harmonic distortion (THD) in inverter systems, comparing square wave, phase shift, and multilevel inverters. The performance of inverters is crucial for efficiently converting direct current (DC) to alternating current (AC), especially in renewable energy applications and electric vehicles. The research identifies gaps in understanding THD performance across different inverter configurations under various input conditions and modulation techniques. Utilizing MATLAB/Simulink, the study simulates a proposed multilevel inverter's output voltage characteristics in both filtered and unfiltered scenarios. The objectives include stimulating THD performance under square wave inputs, SPWM and phase shifts while analyzing the multilevel inverter's output voltage. Findings aim to enhance inverter designs for better power quality and efficiency, highlighting multilevel inverters' advantages over traditional two-level inverters. The implications of filtering techniques on voltage quality are also discussed, contributing valuable insights to the field of power electronics.
subject: Articles
  topic: section
subject: Total Harmonic Distortion
  topic: keywords
subject: 5-level multi-inverter
  topic: keywords
subject: PWM
  topic: keywords
subject: Square wave
  topic: keywords
subject: Phase Shift
  topic: keywords
subject: SPWM
  topic: keywords
creator: Mohamed Faizal Othman
creator: Afarulrazi Abu Bakar
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-06-27
publication date: 2025-06-27
starting page: 19
ending page: 28

Banana Leaf Disease Classification Using SqueezeNet, AlexNet and MobileNet
type: item
description: Banana production is a vital component of global agriculture, facing significant challenges due to various leaf diseases. These diseases can cause substantial yield losses, impacting both farmer livelihoods and industry development. Early and accurate disease detection is crucial for implementing effective management strategies. This study explores the application of Convolutional Neural Network (CNN) for banana leaf disease classification. Three pre-trained CNN architectures, SqueezeNet, AlexNet, and MobileNet, were evaluated for their ability to distinguish between Black Sigatoka, Fusarium Wilt, and healthy banana leaves. A comprehensive dataset containing 3000 images per class was employed for training and testing, with an 8:1:1 train-validation-test split. Performance evaluation metrics included accuracy and loss rate. Among the evaluated models, MobileNet achieved the highest accuracy (94.89%) and the lowest loss (0.1484), demonstrating its effectiveness in banana leaf disease detection. These findings suggest the potential of CNNs as a valuable tool for precision agriculture applications.
subject: Articles
  topic: section
subject: Banana Leaf Disease
  topic: keywords
subject: Image Processing
  topic: keywords
subject: Convolutional Neural Netwrok (CNN)
  topic: keywords
subject: SqueezeNet
  topic: keywords
subject: AlexNet
  topic: keywords
subject: MobileNet
  topic: keywords
creator: Mun Zheng Chong
creator: Nik Shahidah Afifi Md Taujuddin
creator: Suhaila Sari
creator: Zarina Tukiran
creator: Ahmad Raqib Ab Ghani
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-06-27
publication date: 2025-06-27
starting page: 48
ending page: 58

Design of an Off-Grid Hybrid Power Generation System for a Telecommunication Base-Transceiver Station: A Case Study of Cell Site at Oke-Imobi, Nigeria
type: item
description: Hybrid of energy resources has proved to be an innovative means of providing off-grid power to infrastructures in remote locations where there is limited access to the national power supply grid. Adopting a mix of renewable energy resources with battery backup, and gas generator, to determine the optimum mix of the energy resources to meet particular load demands is a major challenge. Load profile for the case cell site was used as input to the simulation software, HOMER (evaluation version), to simulate the mix of energy resources to meet optimum power supply requirement. For cost effective power solution, the optimum period of 4–6 hours per day and a converter of 3 kW were used to obtain the following results for various mix: use of solar, wind and gas generator with 78.4 hours Autonomy produced 6,319 kWh/yr, in excess by 1694 kWh/yr (26.8%), Zero Unmet load and Capacity Shortage; use of solar and gas generator with 85.3 hours Autonomy produced 6,126 kWh/yr., in excess by 1526 kWh/yr (24.8%), with Zero Unmet load and Capacity Shortage; use of wind and gas generator with 177 hours Autonomy produced 5043 kWh/yr in excess by 198 kWh/yr (3.92%), Zero Unmet load and Zero Capacity Shortage; and, the use of solar and wind with 19.7 hours Autonomy produced 4,509 kWh/yr in excess by 632 kWh/yr, (14%), Unmet load of 621 kWh/yr and Capacity Shortage of 811 kWh/yr. Therefore, for the study area, the use of wind and gas generator produced the optimal supply of highest autonomy and minimal excess power with unmet load and zero capacity shortage.
subject: Articles
  topic: section
subject: Hybrid power supply
  topic: keywords
subject: Basic infrastructure
  topic: keywords
subject: Geographical location
  topic: keywords
subject: Cell sites
  topic: keywords
subject: Off-grid power
  topic: keywords
subject: Energy resources
  topic: keywords
creator: Patrick Olabisi
creator: Olusola Ajayi
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-06-27
publication date: 2025-06-27
starting page: 29
ending page: 47

Analyzing Voltage Stability in IEEE 57-Bus System Using Voltage Collapse Proximity Index (VCPI)
type: item
description: The comprehensive study highlights how power systems have evolved over the decades to meet the growing demand for electricity. Increasing energy consumption has made maintaining voltage stability a significant challenge. As a result, voltage stability has become a critical parameter that requires in-depth analysis in modern power systems. This research aims to improve voltage stability analysis in the IEEE 57-bus system using VCPI analysis to identify the weakest buses, enhancing the accuracy of stability assessments and reducing the risk of voltage instability. The proposed methodology utilizes MATLAB software to conduct the power flow analysis, followed by the Voltage Collapse Proximity Index (VCPI) analysis to pinpoint the weakest bus in the 57-bus network. Bus 18 was observed to have the highest VCPI value of 1.0359 pu, signifying it as the weakest bus in the network. It is recommended to apply voltage stability techniques like VCPI for a more comprehensive analysis. Instead of relying on initial values such as voltage magnitude, VCPI provides a reliable measure for assessing the risk of voltage instability, offering valuable insights for future research.
subject: Articles
  topic: section
subject: IEEE 57-bus system
  topic: keywords
subject: Power flow analysis
  topic: keywords
subject: Voltage Collapse Proximity Index (VCPI)
  topic: keywords
subject: Weakest bus
  topic: keywords
subject: Voltage stability
  topic: keywords
creator: Nurfaraliyana Samburi
creator: Ahmad Fateh Mohamad Nor
creator: Suriana Salimin
creator: Nur Ellysa Mu’izz Mohd Zaini
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-06-27
publication date: 2025-06-27
starting page: 10
ending page: 18

IoT-Enabled Bus Tracking System for Real-Time Campus Transportation
type: item
description: Transportation is a utilitarian means by which individuals may move from one location to another. In the present epoch of globalisation, transport plays a vital role in the economic development of a country. The statutory basis for accountability of a public service corporation is now ensuring the delivery of excellent and high-quality service. Currently, students, particularly those who do not have their own means of mobility, rely on school transportation to navigate the campus. However, an issue emerged when students were unable to retrieve the position and location while the bus was in motion. Users have difficulty due to the uncertainty of the bus's arrival schedule, which necessitates an indefinite waiting period. We developed an Internet of Things (IoT) based bus tracking system for Universiti Tun Hussein Onn Malaysia (UTHM) to resolve the problem. This system enables users to conveniently receive real-time information about the bus's current position, location, and estimated arrival time at each stop. The researcher used the Design Thinking Process (DTP) paradigm in this study. The process consists of five steps: empathy, deciding, ideation, prototyping, and testing. The analysis's results validate the successful development and planned operation of the system. Furthermore, the system has the capability to display the precise position and location of the bus, in addition to providing consumers with useful information. The accompanying questionnaire supports this claim, indicating that 32 students, which accounts for 95% of the target audience, have confidence in the product's ability to work well. Ultimately, the IoT-enabled bus tracking system implemented at UTHM effectively accomplished all of its predetermined objectives.
subject: Articles
  topic: section
subject: Bus Tracking System
  topic: keywords
subject: IoT Technology
  topic: keywords
subject: Design Thinking Process
  topic: keywords
creator: Ikhwan Hafiz Bahrum
creator: Saifullizam Puteh
creator: Muhammad Aiman
creator: Nur Anis Aqilah
creator: Ellya Maisarah
creator: Rosnawati Buhari
creator: Hortoyo
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 42
ending page: 52

IoT-Based Automated Cabinet System for Drugs Storage and Accurate Retrieval for Operation Theater Application
type: item
description: Modern healthcare facilities, especially operation theaters, rely on a multitude of medications to ensure the well-being of patients during surgical procedures. In traditional operation theater environments, medications are typically stored in locked cabinets or storage units, with healthcare professionals manually retrieving and dispensing them as needed. This manual approach can be time-consuming, error-prone, and may lead to delays in urgent medical procedures. Thus, the development and implementation of an "IoT-Based Automated Cabinet System for Drugs Storage and Accurate Retrieval for Operation Theater Application” tailored for drug storage and retrieval in operation theaters becomes imperative and is proposed in this work. The system comprises three main components: a storage compartment system, a storage locking system, and a drugs retrieval system. These components are seamlessly integrated with an ESP32 Wi-Fi module and two Arduino Uno microcontrollers. In order, to enhance security, the automated cabinet system incorporates a three-level security feature. This includes AS608 fingerprint sensors and an S-60 electromagnetic lock, ensuring that only registered users can access the cabinet. The system leverages the Kodular application, which integrates with a Google Sheet Database for user authentication and administration. Experimental results demonstrate that it efficiently retrieves correct and substitute drugs, allowing healthcare professionals to monitor drug availability. In addition, it is shown that the HC-SR04 ultrasonic sensor system is efficient in tracking intended drugs within the storage compartment. The system also updates the remaining drug balance using Firebase Database, providing a reliable and efficient solution for operation theater applications. In a nutshell, by integrating various sensors and IoT technologies, this automated cabinet system significantly improves drug retrieval accuracy and efficiency, thereby enhancing patient safety an…
subject: Articles
  topic: section
subject: Automated cabinet system
  topic: keywords
subject: drugs storage
  topic: keywords
subject: ultrasonic sensor
  topic: keywords
subject: Kodular application
  topic: keywords
subject: Firebase Database
  topic: keywords
subject: Google Sheet Database
  topic: keywords
subject: IoT
  topic: disciplines
subject: Electrical and Electronic Technology
  topic: disciplines
subject: medical electronics
  topic: disciplines
creator: Sivenesh Balachandran
creator: Shaharil Mohd Shah
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-01-01
publication date: 2025-01-01
starting page: 17
ending page: 28

A Smart Chair for Sitting Postures Monitoring and Seat Occupancy Detection
type: item
description: In recent years, occupational roles often require extended periods of sedentary activity, particularly sitting in front of computer screens. Incorrect sitting postures adopted during such activities can lead to various health issues such as muscular imbalances and spinal misalignment. Therefore, a Smart Chair for Sitting Postures Monitoring and Seat Occupancy Detection is proposed in this work to overcome those health issues. The Smart Chair design incorporates four ultrasonic sensors to actively monitor the distance between the user’s back and the seat cushion. When poor posture is detected, the Blynk application sends alert notifications to the user’s mobile phone. Additionally, the seat occupancy detection system, powered by four Force Sensing Resistor (FSR) sensors, proves useful in multi-user environments. Real-time alerts via the Blynk application enhance the operational efficiency of the Smart Chair. Validation assessments conducted with three volunteers of varying heights and weights confirmed the effectiveness of the ultrasonic sensors in monitoring sitting postures. The sensors operate consistently with the predefined truth table. Additionally, the validation process for seat occupancy detection, using the same volunteers, demonstrates system reliability and responsiveness. Alert notifications are accurately sent to users’ mobile phones upon detecting physical pressure. In a nutshell, the Smart Chair has demonstrated its effectiveness in continuously monitoring sitting postures and detecting seat occupancy which contributes to a health-conscious and intelligent seating solution, enhancing the overall user experience.
subject: Articles
  topic: section
subject: Ultrasonic sensors
  topic: keywords
subject: Force Sensing Resistor (FSR)
  topic: keywords
subject: Sitting postures monitoring
  topic: keywords
subject: Seat occupancy detection
  topic: keywords
subject: Blynk application
  topic: keywords
subject: Electrical and Electronic Technology
  topic: disciplines
subject: IoT
  topic: disciplines
creator: Mohd Syahmi Hilmi Zaharuddin
creator: Shaharil Mohd Shah
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-01-01
publication date: 2025-01-01
starting page: 36
ending page: 55

Simulation of Absorption Cross Section: A Preliminary Study of Infrared Absorption Spectroscopy for Sulfur Dioxide Gas Measurement
type: item
description: Sulfur dioxide (SO2), an unpleasant-smelling toxic gas, is among the six common air pollutants. These gases, particularly Sulfur Dioxide, are released through the combustion of fossil fuels or other materials containing sulfur. This gas can react with other substances in the atmosphere, forming tiny particles that may enter the lungs and lead to similar adverse health effects. Previously, it has been reported that the development of sulfur dioxide gas sensor such as semiconductor, electrochemical, and others show a long response time compared to absorption spectroscopy-based sensor. Thus, the aim of this project is detection of sulfur dioxide using absorption spectroscopy technique in the infrared region. Initially, the infrared region's absorption cross-section of sulfur dioxide was simulated using the Spectralcalc.com® simulator. The validity of the simulation results was established by comparing them to previous research. The deviation of less than 1% was obtained for the value of absorption cross section. Thus, it indicates the suitability of the Spectralcalc.com® simulator for obtaining the value of absorption cross section in the infrared region. Then, simulations were conducted to analyze the effects of pressure on the absorption cross-section, ranging from 800 mbar to 1200 mbar. According to the simulation, the wavelength at 1412 cm-1 exhibited minimal pressure effect, making it conducive for accurate sulfur dioxide concentration calculation.
subject: Articles
  topic: section
subject: Absorption spectroscopy
  topic: keywords
subject: absorption cross section
  topic: keywords
subject: infrared
  topic: keywords
subject: sulfur dioxide gas
  topic: keywords
subject: Spectralcalc.com
  topic: keywords
creator: Syahidah Sharplee
creator: Maslina Yaacob
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-01-01
publication date: 2025-01-01
starting page: 29
ending page: 35

IoT-Based Smart Liquid Medicine Dispenser for Dysphagia Symptom Patients
type: item
description: Since the onset of the COVID-10 pandemic in Malaysia from 2020, a significant shortage of medical staff has been revealed due to the rising number of patients. Especially when Movement Control Order (MCO) finished, the critical ill patients such as patient with heart disease, kidney failure, stroke, and diabetes returned to emergency departments, causing the medical staffs overwhelming. Additionally, the issue of shortage of nurses in Malaysia had always been the major problem. With the rising of patients, the workload of existing nurses in Malaysia increased and hence directly immense pressure on them. In order to solve the insufficient medical staffs, smart pill box had been invented in the market nowadays. With its automatically dispensing pills and tablets system in time, the patients able to take their medication without the aid of nurses. However, it does not benefit to some groups of patients. For example, elderly, children and the patients with dysphagia symptom, they had difficulty in shallowing pills and tablets. Therefore, the main objective of this project is to design and develop a IoT based smart liquid medicine dispenser that is made of peristaltic liquid pump, DC motor driver module, ultrasonic sensor, and passive buzzer. Additionally, Arduino Cloud IoT Remote application is utilized as the IoT platform. This product will provide the similarities function as the smart pill box, but it is dispensing liquid medicine. Furthermore, this product is designed to offer all the necessary features in an affordable price and it benefits patients with dysphagia symptom as well as children and the elderly with its accurate dispensing of liquid medications. As a result, the prototype able to dispense liquid medicine in the accuracy of 98% to 100%.
subject: Articles
  topic: section
subject: Smart liquid medicine dispenser with IoT
  topic: keywords
subject: ESP32
  topic: keywords
subject: Arduino Cloud IoT Remote application
  topic: keywords
subject: Electrical and Electronic Technology
  topic: disciplines
creator: Cheah Man Lok
creator: Nurmiza Othman
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-01-01
publication date: 2025-01-01
starting page: 1
ending page: 16

Development of Epileptic Seizure Symptoms Detection Device
type: item
description: This paper shows a seizure detection device developed with a pulse oximeter, accelerometer, and vibration sensor. A 9V battery, LM2596 voltage regulator, and two ESP32 microcontrollers were also used in the development process. The pulse oximeter is a sensor whose purpose is to measure the patient's activity level: oxygen saturation, and heart rate. The accelerometer detects motion or activity in a patient's body, which could indicate a possible seizure. On the other hand, a jerky body movement manifested during seizure is detected by the vibration sensor to help in increasing the efficiency of the seizure detection model. The ESP32 microcontroller was interfaced with the sensors in the proposed device to enable data collection and transmission. The LM2596 voltage regulator was added to ensure that power from a 9V battery is always on. The Blynk app provides notifications or alerts to the caregivers whenever there is a seizure. To epileptic patients, this device assures their safety and quality of life because of providing a fast intervention and on-time monitoring. Complete seizure detection is achieved by integrating different kinds of sensors and microcontrollers, while the Blynk app is there to ensure its proper communication with the caregivers for effective and efficient management of the care.
subject: Articles
  topic: section
subject: Seizure
  topic: keywords
subject: Epilepsy
  topic: keywords
subject: pulse oximeter and heart rate sensor
  topic: keywords
subject: vibration
  topic: keywords
subject: Blynk App
  topic: keywords
subject: Acceleration
  topic: keywords
subject: IoT Technology
  topic: keywords
creator: Siti Aishah Zamry
creator: Roshayati Yahya
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-01-01
publication date: 2025-01-01
starting page: 66
ending page: 72

Solar-Powered Smart Bus Shelter in UTHM Campus
type: item
description: This project involves the designing and implementation of solar-powered smart bus shelters within the UTHM campus. The current UTHM bus shelter faces challenges such as lacking real-time information, safety issues due to a lack of lighting support, and bad student experiences while waiting for a bus due to hot or bad weather. Therefore, this project seeks to enhance the students or passengers experience when they want to board on the bus and the bus shelter could provide real-time bus location display, LED lighting, and fans powered by clean solar energy. Incorporating the Internet of Things, the smart bus shelter provides the students with precise real time bus location information that enhances their safety and convenience. Besides that, the smart bus shelter also provides a messenger to notify students which bus approaches which bus shelter in order to reduce the possibility of students missing chances of boarding on the correct bus. The project helps in sustainable development by reducing energy consumption and supporting environmentally friendly public transport solutions. By extensive testing and evaluation, the performance and reliability of the prototype are validated, proving its potential in transforming the conventional bus shelter into the intelligent energy-saving system.
subject: Articles
  topic: section
subject: Solar panel
  topic: keywords
subject: Smart Bus Shelter
  topic: keywords
subject: Internet of Things (IoT)
  topic: keywords
subject: Arduino Cloud
  topic: keywords
subject: Arduino IDE
  topic: keywords
subject: Real-Time GPS
  topic: keywords
creator: Xian Ming Chong
creator: Nurmiza Othman
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-01-01
publication date: 2025-01-01
starting page: 56
ending page: 65

Indoor Location Sensing Using Multiple Wireless Standards
type: item
description: Indoor location sensing systems are crucial for Internet of Things advancements, providing essential location-based information for large-scale applications and systems. The existing literature usually involves designing and testing systems using a single wireless standard. Therefore, it is still uncertain what is the best wireless standard for indoor location sensing and whether there are any benefits to implementing cooperative location sensing. Therefore, an indoor location sensing system was developed, utilizing the RSSI fingerprinting method with K-Nearest Neighbours algorithm. The system was used to evaluate the individual performance of Wi-Fi, Bluetooth and ZigBee for indoor location sensing as well as validate if cooperative location sensing is feasible. For testing purposes, the test sites were split into grids of 1.5m by 1.5m size and the system made predictions on the correct grid position of the user device. The indoor location sensing system developed has an accuracy of 1.5m for a detection range of 10m. In terms of prediction accuracy, the system managed to achieve a maximum accuracy of 80.56% in non-Line of Sight scenario and a maximum accuracy of 100.00% in Line of Sight scenario. The prediction accuracy performance of the system in predicting the correct grid position varies depending on the combination of wireless standards used, with the best accuracy result being 100.00% when using a combination of Wi-Fi, Bluetooth and ZigBee in a Line of Sight scenario.
subject: Articles
  topic: section
subject: internet of things
  topic: keywords
subject: rssi fingerprinting
  topic: keywords
subject: k-nearest neighbour
  topic: keywords
subject: wi-fi
  topic: keywords
subject: bluetooth
  topic: keywords
subject: zigbee
  topic: keywords
creator: Shawn Zhu Wen Tan
creator: Solahuddin Yusuf Fadhlullah
creator: Choon Min Cheong
creator: Samihah Abdullah
creator: Shabinar Abdul Hamid
rights: Copyright (c) 2024 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2024-06-30
publication date: 2024-06-30
starting page: 1
ending page: 15

Bi- Level Optimization of Multi-Microgrids: A Review Considering Demand Response Aggregators
type: item
description: The increased penetration of renewable energy sources (RES) and electric vehicles (EVs) in addition to the non- renewable energy sources such as microturbine (MT), combined heat and power (CHP) and diesel generator (DEG) must have a coordinated operation for achieving optimal energy management system (EMS) and operation of microgrids. The demand side management (DSM) can be utilized using demand response program (DRP) becomes an essential work to deal with distributed generation (DG) that are integrated with distribution grid to minimize the cost of operation and maximizing the profit of microgrids owners (MGO), this can be achieved by exchanging data between MGO and distribution system operator (DSO). The optimal operation of microgrid is subject to various constraints that must not be violated. The complication of the energy management is due to the uncertainties of RES, electricity prices and EVs state of charge (SoC) and arrival/departure time, have to be solved with a stochastic based modeling. The demand response aggregator (DRA), electric vehicles aggregator (EVA) and energy storage system (ESS) are an important player in microgrid optimization that have to be studied thoroughly as they participate in DSM to modify the load demand pattern. The review assists the authors to find the latest achievements in microgrids management.
subject: Articles
  topic: section
subject: Microgrid
  topic: keywords
subject: distributed energy resources
  topic: keywords
subject: demand side management
  topic: keywords
subject: microgrid owner
  topic: keywords
subject: distribution system operator
  topic: keywords
subject: electric vehicles
  topic: keywords
creator: Adel Ridha Othman
creator: Ziyodulla Yusupov
creator: Muhammet Tahir Guneser
rights: Copyright (c) 2025 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-06-27
publication date: 2025-06-27
starting page: 1
ending page: 9

Sustainable Water Solutions: Solar- Driven Distillation and Real-Time Monitoring for Rural Community
type: item
description: In an era characterized by rapid population growth and urban sprawl, access to clean water has become a significant concern for societies around the globe. As the world's most precious resource, water scarcity poses a significant challenge to the sustainability of our planet's ecosystems, economies, and human health. However, despite this issue of modernity, the demand for clean water in rural areas is more pressing and must be taken seriously in order to involve the demands of relevant and up to date processes. Therefore, in-depth studies to maintain quality water for this concern area have become increasingly popular and received the attention of many parties. Thus, the seawater distillation method powered by solar panels has been identified as the most effective technological alternative, accessible source of supply and is able to produce more consistent results. The specific methodology implemented involves several components and processes such as 12V solar panels, batteries, inverters, heating coils, water pumps, charging controllers, microcontrollers, sensors, liquid crystal displays and 2-channel relay modules. Next the target for this work is that the evaporation process will take place and the condensing unit will store the distilled water in a specified container. Subsequently, observe the results of the experiment by measuring the water level at different times and finally it is expected that the water level will increase as the hours increase.
subject: Articles
  topic: section
subject: Water Distillation, Solar Powered, Evaporation, Condensation, Rural, Seawater.
  topic: keywords
creator: Annis Farhana Raymedin
creator: Fathullah Mohammed Fathullah Alqamoudi
creator: Khasyfee Ihtifazhuddin Jasmee
creator: Muhammad Aliff Hafeez Azman
creator: Nurfaraliyana Samburi
creator: Mahyuzie Jenal
rights: Copyright (c) 2024 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2024-06-30
publication date: 2024-06-30
starting page: 64
ending page: 69

Hardware Implementation of the Activation Layer and Mean Pooling Layer for the CNN Digit Recognition
type: item
description: This work focuses on enhancing the efficiency of Convolutional Neural Networks (CNNs) for digit recognition through dedicated hardware design of the ReLU activation function and mean pooling layer. The CNN model is initially implemented in MATLAB and trained on the MNIST dataset. The hardware architecture, designed using Verilog HDL for an Intel Cyclone IV E FPGA, successfully replicates the MATLAB outputs, as verified through rigorous simulations with ModelSim. The hardware implementation demonstrates significant performance improvements, notably reducing execution time from 104,458µs in software to 8.05µs in hardware. The designed hardware exhibits a 2.60GHz frequency, 4,457 logic elements, 2,522 registers, 409,600 memory bits, and 71.73mW thermal power dissipation, showcasing superior computational efficiency.
subject: Articles
  topic: section
subject: Deep Learning, CNN Digit Recognition, Hardware CNN, Pooling Layes, FPGA, Hardware Accelerator
  topic: keywords
creator: Chessda Uttraphan Eh Kan
creator: Araveindran Sithamparam
rights: Copyright (c) 2024 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2024-06-30
publication date: 2024-06-30
starting page: 35
ending page: 41

Portable Environmental Monitoring System using IOT (PEMS)
type: item
description: Air pollution, which is a major health and environmental hazard, is caused by various factors such as industrial, transportation, and domestic activity. The Air Quality Index (AQI) is used as an indication of air quality and potential health dangers to increase public awareness. This work proposed a Portable Environmental Monitoring System using IoT (PEMS) to monitor the air quality parameters and mapping them to the AQI rating and CO2 concentration. PEMS performs three major functions which are to measure the particulate matters, carbon dioxide (CO2) concentration and flammable gases. The Blynk application is used for the monitoring of the gathered data, which is also stored in its database. The values of PM1, PM2.5 and PM10 in μg/m3 are measured by using PMS5003 Particulate Matter. Meanwhile, the CO2 concentrations are obtained by using MQ-135 Air Quality sensor and flammable gases such as Butane and Propane are detected by using the MQ-6 Gas sensor. Based on the experiments, Parit Raja Industrial Estate exhibits the highest average of PM1, PM2.5 and PM10 values due to its industrial surroundings. TDI Residential College comes second due to tenant occupancy and smoking activities. Conversely, PTTA Library at UTHM has the lowest PM values due to its spacious area and good air circulation. In terms of CO2 concentration, Parit Raja Industrial Estate records the highest values due to anthropogenic CO2 influence, while TDI Residential College follows closely, influenced by tenant exhalation and poor air circulation. Meanwhile, the PTTA Library, UTHM maintains the lowest CO2 concentration due to its spacious area and efficient air circulation. Therefore, it is shown, based on the results, that PEMS has provided vital data on air quality parameters, thereby contributing pivotal information to assess the environmental health status, particularly in terms of the AQI.
subject: Articles
  topic: section
subject: PEMS
  topic: keywords
subject: AQI
  topic: keywords
subject: Particulate matter sensor
  topic: keywords
subject: Air quality sensor
  topic: keywords
subject: Gas sensor
  topic: keywords
creator: Zul Helmy Izzani Rokhmad
creator: Shaharil Mohd Shah
rights: Copyright (c) 2024 Journal of Electronic Voltage and Application https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2024-06-30
publication date: 2024-06-30
starting page: 77
ending page: 90