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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 64 Documents
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Search results for , issue "Vol 36, No 1: October 2024" : 64 Documents clear
Customized convolutional neural networks for Moroccan traffic signs classification Khalloufi, Fatima Ezzahra; Rafalia, Najat; Abouchabaka, Jaafar
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp469-476

Abstract

Recognition of traffic signs is a challenging task that can enhance road safety. Deep neural networks have demonstrated remarkable results in numerous applications, such as traffic signs recognition. In this paper, we propose an innovative and efficient system for recognizing traffic signs, based on customized convolutional neural network (CNN) developed through hyperparameters optimization. The effectiveness of the proposed system is assessed using a novel dataset, the Moroccan traffic signs dataset. The results show that the proposed design recognizes traffic signs with an accuracy of 0.9898, outperforming several CNN architectures such as VGGNet, DensNet, and ResNet.
Smart grid solutions for sustainable photovoltaic-electric vehicle integration in Bangladesh Hossain, Al Amin; Samad, Abdus
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp1-14

Abstract

Environmental concerns and the depletion of fossil fuel supplies are driving the rapid integration of photovoltaic (PV) systems into the electrical grid and electric vehicles (EVs) into the transportation sector. Issues like unpredictable power outages and shifts in demand require a cost-benefit analysis and efficient scheduling. In order to optimize PV power consumption and EV charging while taking seasonal variations into consideration, this study offers a novel solar-based grid-tied charging station with an improved scheduling technique. The existing charging station connected to the grid and solar promises not only reduced grid demand and cost savings, but also energy independence and environmental benefits. In the actual case in Rajshahi, Bangladesh, it is carried out using a Homer Grid case study. Bangladesh may promote environmental sustainability and resource conservation with this technology.
Expert systems in mental health: innovative approach for personalized treatment Andrade-Arenas, Laberiano; Rubio-Paucar, Inoc; Celis, Domingo Hernández; Yactayo-Arias, Cesar
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp414-427

Abstract

Custom classification of mental illnesses has emerged as a challenge for mental health specialists, often minimized by patients' lack of awareness of symptoms and the importance of early intervention. Therefore, the purpose of this research is to provide a comprehensive understanding of personalized treatment, encompassing both pharmacological and non-pharmacological options, specifically tailored to mental disorders, considering factors such as the patient's age and gender, among other relevant characteristics. In this context, the Buchanan methodology has been chosen as the framework for structuring a web-based expert system. This approach covers everything from problem identification to system implementation and subsequent evaluation. The survey results, with a total of 50 responses, reveal that the category "Good" leads with 70%, closely followed by "Fair" and "Poor," both at 14%. 71.4% of responses reflect a positive evaluation, with 85.7% combining "Good" or "Fair" responses, and all categories reaching 100%. These results support the feasibility and effectiveness of implementing a web-based expert system under the Buchanan methodology. A positive response in the survey suggests that this methodology can significantly contribute to personalizing and recommending appropriate treatments, both pharmacological and non-pharmacological, thereby benefiting a broad spectrum of patients with mental disorders.
Enhanced fault identification in grid-connected microgrid with SVM-based control algorithm Nair, Divya Shoba; Rajeev, Thankappan Nair; Miraj, Sindhura
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp115-126

Abstract

The penetration of renewable energy sources, electric vehicles (EVs) and load dynamics, and network complexities often lead to nuisance tripping in grid-connected microgrids. Traditional protection methods fail to discriminate fault and other dynamic volatilities in the system. The paper presents a novel two-level adaptive relay algorithm to avoid nuisance tripping in a grid-connected microgrid under varying grid dynamics. The novelty of the adaptive relay algorithm is that nuisance tripping is eliminated by precisely determining normal system-level dynamics at the first level using a phase deviation reference block. The first level determines the necessity for activating the second level, which consists of a detection scheme combining a multiclass support vector machine (SVM) and discrete wavelet transform (DWT). The hybrid DWT-SVM methodology ensures effective fault diagnosis, adapting to variations in energy sources, load fluctuations, and fault scenarios. Real-time hardware-in-the-loop (HIL) simulation validates the system’s effectiveness in dynamic microgrid environments. Extensive experiments on scenarios, including faults, fluctuations in renewable energy generation, and intermittent simulations of EV charging and capacitor switching, were conducted to test the efficacy of the adaptive relay algorithm. Finally, experiments using OPAL-RT HIL real-time simulator and the Raspberry Pi microcontroller validated the adaptive relay algorithm in a grid-connected microgrid under varying grid dynamics.
An improved surface solar radiation estimation model using integrated meteorological-air quality data Boottarat, Prakaykaew; Bin Salim, Mohd Azli; Photong, Chonlatee
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp347-356

Abstract

This paper proposes an improved high-precision surface solar radiation estimation model using the integration of the local meteorological data and air quality index based linear regression analysis. The proposed model was evaluated and compared to 8 conventional models and one generated by the commonly used PVsyst simulation software. The actual solar radiation, meteorological data and air quality index collected over 10 years (during 2011-2021) from standard measuring stations located at the northern zone of Thailand were used for developing the models while the collected data year 2022 were used for validating the developed models compared to the conventional models. The statistical error estimations in terms of mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and mean absolute percentage error (MAPE) were used for the precision evaluation. The study found that the proposed models achieved better prediction results and the highest precision for monthly estimating of solar radiation than the other models by having the highest estimation precision of 94.70-97.19% compared to 87.53-96.74% of the conventional models and 90.38-95.96% of the PVsyst program.
Improving communication between can-sized satellite and ground control station for accuracy of data acquisition Bin Zohari, Mohd Hakimi; Yin, Lam Hong; Bin Mokhtar, Mohd Hezri
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp197-204

Abstract

The can-sized satellite, ScoreSAT satellite is a small communications satellite. ScoreSAT helps to develop a platform for finding directions and the exact spot where a lack of communications signal occurs, as well as a real-time visual feed for analysis of communication during and after landing. The project focuses on the design of ScoreSAT and provides a real-time system for capturing real-time data during descent. The objective of the real-time system is to improve the accuracy and location of ScoreSAT data collection, which can provide pressure, humidity, temperature, altitude, latitude, and longitude readings. The main components of this platform are the hardware design that comprises the flight controller, GPS module, and telemetry kit, the software design, which are Mission Planner, and the real-time system (RTS). Based on the entire research, the compact design of the ScoreSAT and ground station was developed to provide alternative meteorological parameter monitoring to complement primary meteorology ground observation such as weather station and radiosonde and to enhance the reliability of the remote sensing observation for environmental studies concerning the factors determining the environment and atmospheric.
Interlined dynamic voltage restorer using time-domain methodologies with Z-source inverter/voltage source inverter Anuradha, Chandrasekar; Raman, Rathinam Anantha; Arunsankar, Ganesan; Joel, Maharajan Robinson; Sathyanathan, Pitchamuthu; Kantari, Hanumaji; Murugan, Subbiah
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp15-25

Abstract

Electronic devices and loads are very sensitive to the voltage disturbances like voltage sag and voltage swell. Significant financial losses and safety issues may emerge from voltage sags and interruptions, which can be caused by variables such as system breakdowns and load changes. In order to protect against voltage fluctuations and keep vital loads running, dynamic voltage restorers (DVRs) have become more popular. To mitigate the voltage disturbances, an interlined DVR (IDVR) using a Z-source inverter (ZSI) is developed to protect the sensitive devices and loads. Back-to-back DVR connects the distributed feeders with a common direct current (DC) link. The IDVR compensates for the sag voltage and supplies the energy to control the power flow. In addition, proposed a modified synchronous reference frame (MSRF)/direct quadrature theory, hysteresis controller, and proportional integral (PI) controller, which provides the required amount of control signals for a ZSI and voltage source inverter (VSI). MATLAB/Simulink validated the simulation results. The experimental findings show that the suggested system can be implemented successfully and is effective at reducing voltage dips and interruptions, allowing crucial loads to keep operating consistently and without interruption in residential as well as commercial environments.
Digital transformation technologies for conveyor belts predictive maintenance: a review Santoshi Anusha, Pediredla Veni; Peravali, Swapna; Koti Reddy, Dodda Venkata Rama
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp639-646

Abstract

The availability of condition-monitoring data has increased due to internet of things (IoT) technologies, providing information on various parameters like vibration, temperature, current, and voltage. Cloud computing and big data facilitate the prevention of failures and estimation of remaining useful life through advanced mathematical models and artificial intelligence (AI) techniques. These enable prompt and suitable maintenance actions. This article conducts a systematic review of digital transformation technologies, including cloud computing, edge computing, AI, machine learning (ML), and TinyML, in predictive maintenance for conveyor belt systems. This article reviews how these digital transformation technologies improve predictive maintenance strategies for conveyor belts. The systematic review summarizes the results and challenges of various methodologies used in conveyor belt systems and suggests areas for further research. This paper aimed to serve as a useful resource for researchers, practitioners, and industry professionals seeking insights into current predictive maintenance technologies for conveyor belt systems. The takeaways of the review are expected to ignite discussion on efficient and proactive maintenance strategies and promote the development of innovative solutions for ensuring the reliability and longevity of conveyor belt systems in the digital era.
Tech driven wellness: centralized integrated health management system in UAE Dakwar, Mohamad Fadi; Dakwar, Norseen Fadi; Ali, Halah Yaseen; Shaker, Yomna O.
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp583-591

Abstract

With the ever-more increasing usage of technology in our day-to-day life, an incursion into healthcare has been warranted. Especially in today’s age, where you have digital trackers all around, confusing terms of service, and just in general difficult management of healthcare. HealthPulse seeks to revolutionize that and simplify the concept of healthcare to the simple person. This will be accomplished by integrating the application with the Emirates ID, in the United Arab Emirates, and granting access to various insurance and past records. Additionally, it features a section for early diagnoses and standard measurements, in addition to extensions and plugins to be provided by third parties. Using biometrics will apply in the implementation for the creation of a secure digital national ID and enhancing the merger of public. Machine learning framework, which is trained on a dataset of images of certain diseases will be able to differentiate between a healthy and inflicted cases.
A novel steady-state visually evoked potential-based brain-computer interfaces using trans-subject feature fusion approach Krishnappa, Manjula; Anandaraju, Madaveeranahally B.
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp392-400

Abstract

A brain-computer interface (BCI) is a transformative technology that enables users to control external devices or communicate solely through the analysis of their brain activity. One promising aspect of BCIs is the utilization of steady-state visually evoked potentials (SSVEPs), a neurophysiological response in the brain that synchronizes with repetitive visual stimuli. This paper introduces a novel approach known as the trans-subject feature fusion approach (TFA), designed to improve SSVEP-based BCIs. This methodology streamlines data pre-processing, creates invariant SSVEP templates, and simplifies calibration, addressing key challenges that have hindered BCI adoption. By doing so, the main aim is to contribute to the advancement of BCIs, making them more accessible and efficient for a range of applications, from assistive technologies to healthcare, ultimately enhancing users’ communication, and control capabilities.

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