1
University of Sfax, National School of Electronics and Telecommunications of Sfax, BP 1173, Sfax, 3038, Sfax, Tunisia
(munir.iq@gmail.com)
2
Department of Information Systems, Faculty of Computing and IT, Northern Border University, Rafha, Saudi Arabia
( Mohamed.Ammar@nbu.edu.sa; )
3
Faculty of Sciences, University of Sfax, Sfax, Tunisia
(monji.kherallah@fss.usf.tn)
4
Faculty of Sciences, University of Sfax, Sfax, Tunisia
(fahmi kammoun@yahoo.fr)
Abstract :
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.
Keywords :
Internet of Things (IoT); Smart Fuel Filling Systems , Machine Learning; Performance Evaluation; Real-world Deployment; User Feedback; System Bottlenecks; Operational Challenges; Resource Management Efficiency; User Experience.
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| Style | # |
|---|---|
| MLA | Muneer Sadeq ALqazan, Mohamed Ben Ammar, Monji Kherallah , Fahmi Kammoun. "Performance Evaluation and Real-world Challenges of IoT-Based Smart Fuel Filling Systems with Embedded Intelligence." Fusion: Practice and Applications, Vol. 14, No. 2, 2024 ,PP. 56-67 (Doi : https://doi.org/10.54216/FPA.140204) |
| APA | Muneer Sadeq ALqazan, Mohamed Ben Ammar, Monji Kherallah , Fahmi Kammoun. (2024). Performance Evaluation and Real-world Challenges of IoT-Based Smart Fuel Filling Systems with Embedded Intelligence. Journal of Fusion: Practice and Applications, 14 ( 2 ), 56-67 (Doi : https://doi.org/10.54216/FPA.140204) |
| Chicago | Muneer Sadeq ALqazan, Mohamed Ben Ammar, Monji Kherallah , Fahmi Kammoun. "Performance Evaluation and Real-world Challenges of IoT-Based Smart Fuel Filling Systems with Embedded Intelligence." Journal of Fusion: Practice and Applications, 14 no. 2 (2024): 56-67 (Doi : https://doi.org/10.54216/FPA.140204) |
| Harvard | Muneer Sadeq ALqazan, Mohamed Ben Ammar, Monji Kherallah , Fahmi Kammoun. (2024). Performance Evaluation and Real-world Challenges of IoT-Based Smart Fuel Filling Systems with Embedded Intelligence. Journal of Fusion: Practice and Applications, 14 ( 2 ), 56-67 (Doi : https://doi.org/10.54216/FPA.140204) |
| Vancouver | Muneer Sadeq ALqazan, Mohamed Ben Ammar, Monji Kherallah , Fahmi Kammoun. Performance Evaluation and Real-world Challenges of IoT-Based Smart Fuel Filling Systems with Embedded Intelligence. Journal of Fusion: Practice and Applications, (2024); 14 ( 2 ): 56-67 (Doi : https://doi.org/10.54216/FPA.140204) |
| IEEE | Muneer Sadeq ALqazan, Mohamed Ben Ammar, Monji Kherallah, Fahmi Kammoun, Performance Evaluation and Real-world Challenges of IoT-Based Smart Fuel Filling Systems with Embedded Intelligence, Journal of Fusion: Practice and Applications, Vol. 14 , No. 2 , (2024) : 56-67 (Doi : https://doi.org/10.54216/FPA.140204) |