FuelEye an Intelligent IoT Framework for Smart Fuel Management and Distance Prediction in Sustainable Transportation

Abstract

India’s transportation sector, serving 1.4 billion people, grapples with rising fuel costs, reaching ₹95–₹100 per liter for petrol and ₹85–₹90 per liter for diesel in 2025, alongside environmental concerns, contributing 24% to global CO2 emissions. Traditional fuel monitoring systems, such as analog gauges with ±10–15% inaccuracies or costly OBD-II devices priced at ₹30,000–₹50,000, fail to deliver precision and affordability. This research introduces a Smart Fuel Tracking and Distance Estimation System that integrates a Gems Sensors HC-SR04, NEO-6M GPS module, Arduino Uno, and NodeMcu for real-time monitoring via Wi-Fi connectivity. The system achieves ±1% fuel level accuracy and ±5 km distance estimation, designed for India’s varied conditions, from Chennai’s urban traffic to NH44’s highways. A Hidden Markov Model predicts fuel consumption across urban, highway, rural, and idle scenarios, while a Java Swing GUI, MySQL database, and Blynk IoT platform provide seamless visualization and mobile access. Priced at ₹10,000–₹15,000, the system is cost-effective. Testing on a Tata Nexon with a 50-liter tank involving 50 users showed 99.9% uptime, 95% user satisfaction, and 92% prediction accuracy, demonstrating scalability for India’s transportation needs. This innovative solution not only enhances fuel efficiency but also empowers users with real-time insights into their driving behavior.