AI Assisted Engine Oil Monitoring System

Abstract

Abstract: This study presents a pioneering solution aimed at elevating the performance of two-wheelers through the integration of real-time engine oil and fuel level monitoring systems. Recognizing the critical role of these components in determining vehicle efficiency, longevity, and overall user satisfaction, the proposed approach leverages state-of-the-art sensor technologies and connectivity solutions. The real-time engine oil monitoring system constitutes a groundbreaking aspect of this research, employing advanced sensors to continuously assess the quality and viscosity of the engine oil while the vehicle is in operation. The collected data undergoes analysis through sophisticated machine learning algorithms, facilitating the identification of potential issues such as oil degradation or contamination. By providing riders with immediate feedback on the engine oil's condition, the system empowers them to undertake timely maintenance measures, including prompt oil changes. This not only contributes to the extended lifespan of the engine but also enhances overall performance. Simultaneously, the fuel level monitoring system utilizes cutting-edge sensors to accurately measure the remaining fuel in the two-wheeler's tank. This realtime data is communicated to the rider through an intuitive interface, offering precise information on the fuel level and estimated range. This empowers riders to plan their journeys more effectively and contributes to fuel efficiency by minimizing instances of running on low fuel, thereby optimizing refueling intervals.