Design and Implementation of an IoT-Based Smart Fuel Filling System for Efficient Resource Management

Abstract

Oil is a significant driver of the global economy, and the efficient transportation of oil derivatives to petrol stations is crucial for fuel distribution. However, manually running petrol pumps presents several challenges, including the need for labour, accuracy issues, fuel smuggling, fluctuating oil prices, database upkeep, and environmental pollution. This study leverages the capabilities of the Internet of Things (IoT) to detect, communicate, and exchange data autonomously, without human intervention, in order to tackle these issues. The objective of this project is to utilize IoT technology in order to create a sophisticated system for three filling stations. This system will enable the simultaneous monitoring and control of the stations using a web application. The suggested system incorporates an algorithm that enables automatic fuel loading using Radio Frequency Identification (RFID) cards. The platform's encrypted dashboard ensures authorized access through the use of data encryption, employing the Advanced Encryption Standard (AES) algorithm and a hash function. The efficacy of the proposed system is assessed in the Proteus programme using code from the Arduino IDE. This demonstrates its complete automation capabilities, including gas leak prevention, fuel filling, and fire detection and extinguishing. Simulation results demonstrate that our proposed solution surpasses established methods such as Kuhn Munkres (KM) or deep neural network (DNN) techniques as the complexity of the problem increases. Moreover, our proposed scheme surpasses the KM algorithm in terms of execution time, significantly outperforming the DNN technique. This provides a more efficient method for allocating resources in intelligent fuel filling systems. In addition, the system exhibits a high level of precision ranging from 0.075 to 0.025 during petrol filling processes. The system use the Internet of Things (IoT) protocol to capture and store data pertaining to customers, sales, and the environment. This is achieved by connecting all devices and sensors to a centralized node on the Internet. This guarantees comprehensive data administration.

Keywords

• Remote Monitoring.
• Cloud Computing,
• Network,
• Sensor,
• Fuel Efficiency,
• Resource Management,