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Browsing Research Outputs by Author "Adeaga, Oyetunde Adeoye"

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    Investigating fuel adulteration using arduino as an engine protection device (EPD)
    Adigun,Matthew O.; Alabi, Engr Seyi
     | 
    Ajagbe, Sunday AdeolaAdeaga, Oyetunde Adeoye
    2023
     | Hunan University
    This study explores the potential application of an Arduino-based engine protection device (EPD) for detecting tainted gasoline and engine protection. Fuel that has been tampered with can seriously harm engines, raising maintenance costs and lowering fuel efficiency. To look for any irregularities that would indicate fuel adulteration, an Arduino-based EPD can be programed to monitor metrics, including fuel flow rate, temperature, pressure, and quality. However, the precision and sensitivity of the employed sensors, the dependability and toughness of the Arduino platform, and the caliber of the device's programing and calibration will all affect how well an Arduino-based EPD detects gasoline adulteration. In conclusion, with an average mean detection time of 35 s and the ability to find adulteration levels of adulterants in fuel in less than a minute, the use of an Arduino-based EPD to detect fuel adulteration shows promise as a potentially effective and cost-effective solution for protecting engines from damage caused by contaminated fuel. The efficacy of an Arduino-based EPD for detecting gasoline adulteration under various operating circumstances and with various types of fuel needs to be further investigated and tested.
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    Performance of the solar PV module of the dual solar axis tracker of a smart home monitoring system
    Adigun,Matthew O.; Alabi, Oluwaseyi O.
     | 
    Adeaga, Oyetunde AdeoyeAjagbe, Sunday AdeolaAdekunle, Samson Temitope
    2023
     | Hunan University
    Nowadays, solar PV power plays a significant role in sustainable electrification. However, because of the positions of PV modules, the electricity generated by the solar system is drastically reduced. This study aims to design, build, and deploy a dual-axis solar PV tracking system. This study describes a module control tracking system based on artificial intelligence for more effective solar energy harvesting. The passive closed-loop system often employs two opposing solar-powered actuators to receive equal solar radiation only when the mirrors point directly toward the sun to provide feedback from its location. Without using feedback to verify the intended result, the controller enters a mathematical equation into the tracking system using only the current state of the system and the algorithm. The solar tracker system rotates the solar panel toward the sun or another light source using an Arduino board, two DC motors, four light dependent resistors, four resistors, and a monocrystalline panel. In conclusion, the project’s performance after testing satisfied the design criteria and is likely to boost the efficiency of solar panels.
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