Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/2425 2018 2018 University of Sfax, National School of Electronics and Telecommunications of Sfax, BP 1173, Sfax, 3038, Sfax, Tunisia Muneer Sadeq ALqazan Department of Information Systems, Faculty of Computing and IT, Northern Border University, Rafha, Saudi Arabia Mohamed Ben Ammar Faculty of Sciences, University of Sfax, Sfax, Tunisia Monji .. Faculty of Sciences, University of Sfax, Sfax, Tunisia Fahmi Kammoun Integrating the Internet of Things (IoT) with smart fueling systems has the potential to revolutionize the fuel industry, leading to better resource management and increased operational efficiency. With the increasing integration of machine learning techniques, these systems are capable of self-learning, adaptation, and predictive decision making. However, the effectiveness of these advanced systems in real-life situations remains an area of intense interest and research. in operational efficiency and reduces resource waste by 10% compared to conventional systems. Additionally, system bottlenecks were identified mainly in data trans- mission  (delayed by up to 20% in high  traffic cases) and hardware malfunctions due  to environmental factors. End user feedback  indicates a satisfaction level of 85%, with an emphasis on system responsiveness and fuel prediction recommendations. Challenges mainly come from software issues, unwanted environmental interference and  ’some initial resistance from users accustomed to conventional systems. However, with data in hand, the benefits of integrating intelligence into IoT-based fueling systems offer a sustainable and efficient future for the fuel industry. Recommendations are made to improve data transmission channels, develop  robust hardware for extreme conditions, and conduct targeted user education campaigns. 2024 2024 56 67 10.54216/FPA.140204 https://www.americaspg.com/articleinfo/3/show/2425