The Future of Electric Vehicles: Navigating the Intersection of AI, Cloud Technology, and Cybersecurity

Hassan Rehan

doi:10.18535/ijsrm/v12i04.ec04

Abstract

The emergence of electric vehicles (EVs) represents a paradigm shift in transportation, offering not only the promise of reduced carbon emissions but also the potential for enhanced sustainability and innovation. However, the full realization of EVs' transformative capabilities extends beyond mere electrification; it encompasses the integration of state-of-the-art technologies such as Artificial Intelligence (AI) and Cloud Computing. This meticulously crafted research article delves into the profound impact of AI and cloud technologies on the EV landscape within the United States. It meticulously examines how these technological advancements are reshaping EV ecosystems, catalyzing advancements in autonomous driving, optimizing battery management systems, and enriching user experiences. Furthermore, it elucidates the imperative need for robust cybersecurity measures to fortify these sophisticated systems against cyber threats, thereby ensuring the integrity, privacy, and stability of the transportation network.

With a diverse audience in mind, including automotive industry professionals, policymakers, cybersecurity experts, environmental advocates, technology enthusiasts, and the broader public, this article serves as a beacon illuminating the future of transportation, sustainability, and digital security within the realm of EVs. Through a blend of rigorous analysis, insightful commentary, and visionary foresight, it aims to provide profound insights into the trajectory of EV technology in the United States and beyond.

Keywords

Electric Vehicles (EVs)Artificial Intelligence (AI)Cloud TechnologyCybersecurityAutonomous DrivingBattery ManagementUser ExperienceSustainabilityTransportation NetworkAutomotive Industry

References

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[refR-4] Jang-Jaccard, J., & Nepal, S. (2014). A survey of emerging threats in cybersecurity. Journal of computer and system sciences, 80(5), 973-993.Google Scholar ↗

[refR-5] Vermesan, O., John, R., Pype, P., Daalderop, G., Kriegel, K., Mitic, G., ... & Waldhör, S. (2021). Automotive intelligence embedded in electric connected autonomous and shared vehicles technology for sustainable green mobility. Frontiers in Future Transportation, 2, 688482.Google Scholar ↗

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[refR-7] Rehan, H. (2024). AI-Driven Cloud Security: The Future of Safeguarding Sensitive Data in the Digital Age. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 1(1), 47-66.Google Scholar ↗

[refR-8] Song, J., He, G., Wang, J., & Zhang, P. (2022). Shaping future low-carbon energy and transportation systems: Digital technologies and applications. IEnergy, 1(3), 285-305.Google Scholar ↗

[refR-9] Rehan, H. (2024). Revolutionizing America's Cloud Computing the Pivotal Role of AI in Driving Innovation and Security. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 2(1), 189-208.Google Scholar ↗

[refR-10] Sarker, M. (2022). Towards Precision Medicine for Cancer Patient Stratification by Classifying Cancer By Using Machine Learning. Journal of Science & Technology, 3(3), 1-30.Google Scholar ↗

[refR-11] Asaju, B. J. (2024). Enhancing V2X Communication Security Advanced Encryption and Authentication Protocols. Human-Computer Interaction Perspectives, 4(1), 28-56.Google Scholar ↗

[refR-12] Pulicharla, M. R. (2023). Hybrid Quantum-Classical Machine Learning Models: Powering the Future of AI. Journal of Science & Technology, 4(1), 40-65.Google Scholar ↗

[refR-13] Ramirez, J. G. C. (2024). Transversal Threats and Collateral Conflicts: Communities of the United States under the siege of political conflicts on the American continent. International Journal of Culture and Education, 2(1). https://doi.org/10.59600/ijcae.v2i1.14DOI ↗Google Scholar ↗

[refR-14] Asaju, B. J. (2024). Standardization and regulation of V2X cybersecurity: analyzing the current landscape, identifying gaps, and proposing frameworks for harmonization. Advances in Deep Learning Techniques, 4(1), 33-52.Google Scholar ↗

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[refR-17] Pulicharla, M. R. Explainable AI in the Context of Data Engineering: Unveiling the Black Box in the Pipeline.Google Scholar ↗

[refR-18] Salah, K., Hammoud, M., & Zeadally, S. (2015). Teaching cybersecurity using the cloud. IEEE Transactions on Learning Technologies, 8(4), 383-392.Google Scholar ↗

[refR-19] Ahmad, W., Rasool, A., Javed, A. R., Baker, T., & Jalil, Z. (2021). Cyber security in iot-based cloud computing: A comprehensive survey. Electronics, 11(1), 16.Google Scholar ↗

[refR-20] Asaju, B. J. (2024). Cybersecurity Frameworks for Autonomous Vehicle Systems: Safeguarding Onboard Systems, Communication Networks, and Data Privacy in Smart City Ecosystems. Internet of Things and Edge Computing Journal, 4(1), 27-48.Google Scholar ↗

[refR-21] Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., & Ghalsasi, A. (2011). Cloud computing—The business perspective. Decision support systems, 51(1), 176-189.Google Scholar ↗

[refR-22] Lee, Z., Wu, Y. C., & Wang, X. (2023, October). Automated Machine Learning in Waste Classification: A Revolutionary Approach to Efficiency and Accuracy. In Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition (pp. 299-303).Google Scholar ↗