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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
Vigneshwaran, Pandi
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Computer Science & IT Electrical & Electronics Engineering

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Development of an internet of things-based weather station device embedded with O2, CO2, and CO sensor readings Megantoro, Prisma; Saud Al-Humairi, Safaa Najah; Kustiawan, Arya Dwi; Arsalan, Muhammad Rafi Nabil; Prastio, Rizki Putra; Awalin, Lilik Jamilatul; Vigneshwaran, Pandi
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp1122-1134

Abstract

Weather station devices are used to monitor weather parameter conditions, such as wind direction, speed, rainfall, solar radiation level, temperature, and humidity. This article discusses the design of a customized weather station embedded with gas concentration readings, whereby the gas concentration measurement includes oxygen (O2), carbon dioxide (CO2), and carbon monoxide (CO). The measurements and data processing of input sensors were transmitted to an Arduino Uno microcontroller, and the input data were then remitted to Wemos D1 Mini to be uploaded to a cloud server. Furthermore, the gas sensors' characterization methods were also considered to reveal the obtained results of accuracy, precision, linearity, and hysteresis. An android-based mobile application was also designed for monitoring purposes. The system in our experiment utilized an internet connection with a field station, base station, and database server.
Smart measurement and monitoring system for aquaculture fisheries with IoT-based telemetry system Megantoro, Prisma; Anugrah, Antik Widi; Abdillah, Muhammad Hudzaifah; Kustanto, Bambang Joko; Fadhilah, Marwan; Vigneshwaran, Pandi
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6900

Abstract

The instrumentation design of an online monitoring device for aquaculture media is discussed in this article. The main processor in this internet of things (IoT) real-time telemetry system is an ESP32 board. Temperature, acidity level, conductivity level, dissolved oxygen (DO) level, and degree of oxygen reduction in the water were the aquaculture parameters measured. The ESP32 collects data from each sensor, groups it into a dataset, displays it on the LCD, saves it to the SD card, and then uploads it to the real-time database. In addition, an Android application is being developed for users. This device has been tested to ensure that each measured parameter is accurate and precise. The accuracy test, one of the major results of laboratory scale tests, demonstrates that each parameter has a different measurement error that represents with average error absolute. Six tested sensors/instruments were subjected to the test. Average absolute error for temperature sensor is +0.76%, pH sensor is +1.52%, electrical conductivity (EC) sensor is +10.8%, oxidation reduction potential (ORP) sensor is +14.6%, DO sensor is +9.3%, and total dissolve solids (TDS) sensor is +13.2%. This device is very dependable and convenient for monitoring the condition of aquaculture media in real-time and accurately.
Autonomous and smart cleaning mobile robot system to improve the maintenance efficiency of solar photovoltaic array Megantoro, Prisma; Abror, Abdul; Syahbani, Muhammad Akbar; Anugrah, Antik Widi; Perkasa, Sigit Dani; Setiadi, Herlambang; Awalin, Lilik Jamilatul; Vigneshwaran, Pandi
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5950

Abstract

A solar photovoltaic (PV) array is part of a PV power plant as a generation unit. PV array that are usually placed on top of buildings or the ground will be very susceptible to dirt and dust. Thus, this dirt and dust will be able to reduce the performance and work efficiency of the generation unit. Cleaning PV arrays by manpower requires high effort, cost, and risk, especially in higher location. This study presents the design of a mobile robot that is used to replace human labor to clean PV arrays. That way, the PV array maintenance steps can reduce operational costs and risks. This intelligent controlled mobile robot can maneuver safely and efficiently over PV arrays. gyroscope and proximity sensors are used to detect and follow the sweep path over the entire PV array area. Proportional integral derivative (PID) control test makes the robot can stabilize in about 5.72 seconds to keep on the track. The smart PV cleaning robot has average operation time about 13 minutes in autonomous mode and 20-24 minutes in manual mode. The operation of the robot is effective to give more efficiency on the use of energy, time, and maintenance costs of PV array system.
The implementation of Archimedes optimization algorithm for solar charge controller-maximum power point tracking in partial shading condition Perkasa, Sigit Dani; Megantoro, Prisma; Hidayah, Nayu Nurrohma; Vigneshwaran, Pandi
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp2769-2785

Abstract

Maximum power point tracking (MPPT) enhances the efficiency of solar photovoltaic (PV) systems by ensuring optimal power extraction under varying conditions. MPPT is implemented in solar charge controllers or hybrid inverters connected to PV arrays. The current-voltage (IV) curve, influenced by temperature and irradiance fluctuations, becomes more complex under partial shading, causing multiple local maxima and reducing efficiency. This study proposes an MPPT technique using the Archimedes optimization algorithm (AOA), a novel metaheuristic inspired by Archimedes' principle. The AOA-based MPPT integrates a DC/DC buck converter controlled by an STM32 microcontroller to address challenges in complex shading conditions. Comparative analysis demonstrates the AOA's superiority in achieving high efficiency and fast convergence. The AOA-based MPPT achieved an average efficiency of 93.17% across shading scenarios, outperforming PSO (87.04%) and non-MPPT systems (84.56%). It also exhibited faster average tracking times of 90.5 ms compared to PSO's 100.5 ms, ensuring robust and reliable performance. These results confirm the effectiveness of the AOA-based method in maximizing energy harvesting in real-world PV applications.
Modelling and simulation of maximum power point tracking on partial shaded PV based-on a physical phenomenon-inspired metaheuristic algorithm Megantoro, Prisma; Dona Saya, Joy Sefine; Syahbani, Muhammad Akbar; Fadhilah, Marwan; Vigneshwaran, Pandi
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i3.pp1923-1937

Abstract

Maximum power point tracking (MPPT) is a technique to optimize the photovoltaic (PV) current generation, so it can improve the efficiency of solar energy harvesting. MPPT works by searching the voltage which generates the maximum power, called the maximum power point (MPP). MPP value changes by the fluctuance of ambient temperature and solar insolation level depicted by the I-V curve. Searching the MPP will be more complex if the partial shading is happened. The effect of partial shading will rise to more than one local MPPs. In this research, an optimization algorithm is modeled and simulated the MPPT technique in partial shading. The optimization uses the new metaheuristic algorithm which inspired from a physical phenomenon, called Archimedes optimization algorithm (AOA). The AOA uses mathematical modeling which has convergence capabilities, balanced exploration, and exploitation and is suitable for solving complex optimization technique, like MPPT. The research used varies partial insolation percentage. The implementation of MPPT-AOA compared to other metaheuristic algorithms to analysis its performance in the aspect of PV system parameters and tracking process parameters. The simulation result shows that the AOA can enrich the MPPT technique and improve the solar energy harvesting which is superior to other algorithms.
Co-Authors Abdillah, Muhammad Hudzaifah Abror, Abdul Anugrah, Antik Widi Arsalan, Muhammad Rafi Nabil Awalin, Lilik Jamilatul Dona Saya, Joy Sefine Fadhilah, Marwan Herlambang Setiadi Hidayah, Nayu Nurrohma Kustanto, Bambang Joko Kustiawan, Arya Dwi Perkasa, Sigit Dani Prisma Megantoro Rizki Putra Prastio Saud Al-Humairi, Safaa Najah Syahbani, Muhammad Akbar