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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Jurnal ULTIMA Computing
Linelson, Ricardo
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Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Optimizing the position of photovoltaic solar tracker panels with artificial intelligence using MATLAB Simulink Linelson, Ricardo; Rinanda Saputri, Fahmy
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i4.pp4003-4018

Abstract

This research aims to apply an artificial intelligence (AI) system to control the position of photovoltaic (PV) panels to maximize the use of solar energy using the solar tracker. The implementation of AI algorithms to achieve optimal panel orientation, considering factors such as sunlight intensity and sun position is also discussed. The simulation results using matrix laboratory (MATLAB) Simulink can be observed on the scope, displaying the position control graph of the solar panel from sunrise to sunset. By employing proportional integral derivative (PID) control, the error is likely to be minimal, ensuring that the panel will continue to follow the sun until it sets at the maximum point of 4:00 PM. After that, the panel can be adjusted back or reset to the initial position at 6:00 AM for the following day. In a full-day simulation, the solar panel will follow the sun's movement from sunset to sunrise. At the basic level, sunrise occurs in the first hour at position 1.0, which is 6:00 AM in the minimum point at the bottom left corner of the curve, and sunset occurs in the afternoon at position 5.25, which is 4:00 PM at the maximum point in the top right corner of the curve.
Design of a Nutrient and Environment Monitoring IoT Device in Vertical Hydroponic System Linelson, Ricardo; Saputri, Fahmy Rinanda
ULTIMA Computing Vol 17 No 1 (2025): Ultima Computing: Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v17i1.4145

Abstract

This study presents the design and performance evaluation of an Internet of Things (IoT)-based nutrient and environmental monitoring device for vertical hydroponic farming. The system employs multiple sensors to measure pH, Total Dissolved Solids (TDS), nutrient temperature, air temperature, and air humidity. Data are transmitted via ESP32 and integrated with the Arduino IoT Cloud, enabling real-time monitoring through a web dashboard and IoT Remote mobile application. A 10-day testing period was conducted to compare sensor outputs against standard calibrator references. The device demonstrated minimal bias (e.g., 0.20 for pH, 0.51"¯°C for nutrient temperature) and high precision (100.00%) across all parameters. Accuracy ranged from 92.33% (TDS) to 98.24% (nutrient temperature), while error rates were relatively low (e.g., 1.76% for nutrient temperature and 7.67% for TDS). These findings validate the system's reliability and consistency, supporting its potential for scalable implementation in precision-controlled, real-time monitoring applications within urban agriculture.
Techno-economic analysis and optimization of solar energy systems: a case study at Ar-Raniry State Islamic University Saputri, Fahmy Rinanda; Linelson, Ricardo; Salehuddin, Muhammad; Al-Haidar, Muhammad Dzaky
International Journal of Advances in Applied Sciences Vol 14, No 2: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i2.pp322-335

Abstract

This research examines the implementation of a solar power generation system at Ar-Raniry State Islamic University (UIN Ar-Raniry), specifically focusing on the Faculty of Tarbiyah and Keguruan building. The study aims to enhance energy efficiency, assess economic feasibility, and reduce environmental impacts by optimizing solar energy potential through variables such as local meteorological conditions, panel orientation, tilt angles, and system efficiencies. Utilizing PVSyst software for simulations, the research evaluates technical performance, life cycle costs, and carbon dioxide (CO₂) emission reductions. The results indicate that the solar Photovoltaic (PV) system can generate 251,214 kWh annually while reducing CO₂ emissions by 173,095 kg. Economically, the investment is deemed feasible, with a payback period of 7.8 years, a lower cost of energy (LCOE) compared to State Electricity Company (PLN) tariffs, a positive net present value (NPV), and a high internal rate of return (IRR). Although there are minor losses in thermal and module quality, the system remains effective. This study contributes significantly to sustainable energy policies in higher education and recommends further long-term performance monitoring and exploration of additional renewable energy technologies on campus.
Co-Authors Al-Haidar, Muhammad Dzaky Rinanda Saputri, Fahmy Salehuddin, Muhammad Saputri, Fahmy Rinanda