Fuel automata: Smart fuel dispenser using RFID technology and IoT-based monitoring for automotive applications

Abstract

In the modern era, time holds immense value, and individuals strive to avoid delays in their daily responsibilities. These fuel stations are time-consuming and rely on human labour for efficient operation. With each passing day, the number of vehicles and devices in our technologically advanced world continues to grow rapidly. As a result, customers wait in queues at fuel stations, fuelling their desire to transition to an automated fuel dispensing system and eliminate the manual fuel distribution process from their daily routines. This research paper introduces an innovative smart fuel dispenser system that leverages RFID technology and IoT-based monitoring to enhance automotive fuelling processes. By addressing the limitations of conventional fuelling systems, this proposed system provides a superior solution that is more efficient and effective. Notably, it offers numerous benefits, such as improved accuracy, efficiency, safety, and sustainability, thereby presenting potential cost savings for fuel station owners and operators. The ongoing project is focused on automating fuel dispensing stations using RFID technology as a highly efficient tool. This approach aims to reduce the traffic congestion typically seen in front of fuel stations by shortening the time required for fuel dispensing compared to traditional manual operations. To enhance control and monitoring capabilities, an Android application has been created. This app allows for the tracking of fuel transactions and transaction history for both customers and fuel station dealers. The system utilizes NodeMCU and the Android app as an Internet-of-Things platform for seamless communication between the system, customers, and dealers. This study presents concrete evidence that supports the viability and potential advantages of the proposed system, emphasizing its capacity to revolutionize the fuelling industry and mitigate carbon emissions. The findings derived from the implemented system have been thoroughly examined, offering an intelligent solution for a sustainable future.