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Blockchain for Effective Renewable Energy Management in the Intelligent Transportation System

    https://doi.org/10.1142/S0219265921410097Cited by:8 (Source: Crossref)
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    This article is part of the issue:
    Supplementary Issue 1 — Blockchain Assisted Cyber Physical System for Cyber Security
    Guest Editors: BalaAnand Muthu, Imran Shafique Ansari, Xuan Liu (yusuf)

    Abstract

    In intelligent transportation systems (ITS), electric vehicles (EVs) play an essential role in reducing environmental pollution and minimizing high fuel costs. The EVs are three times efficient than conventional gasoline-powered vehicles, whereas it depends on the mix of source generation on the grid utilized for charging. However, in most cases, the EVs are resultant in emitting the more substantial greenhouse gas that extends fossil fuels’ lives. Therefore, the ITS contributing to developing the renewable energy management process is incorporated with electric vehicles to reduce greenhouse gas. The EVs are mostly designed to reduce the cost and improve efficiency during the charging infrastructure. Hence, renewable energies are saved exclusively and eliminating wasteful usage. In this work, a blockchain-based effective renewable energy management process should be created to achieve this goal. The blockchain process validates each EV before permitting them to charge their vehicle. The blockchain principle analyzes the energy demand of any EV and validates its demand through vehicle data. The validation process enables the same and original energy use vessel to be identified to remove threats associated activities efficiently. The validating process considering the vehicle information and energy utilization level to verify the EV. The block-based validation process monitoring each vehicle entered into the grid environment, and the ITS process minimizes the fuel wastage and enhances the system’s overall efficiency.

    References

    • 1. M. Alam, J. Ferreira and J. Fonseca, Introduction to intelligent transportation systems, in Intelligent Transportation Systems (Springer, Cham, 2016), pp. 1–17. Crossref, Google Scholar
    • 2. W. H. Chen, S. H. Chang, K. C. Kao, S. Y. Lin and W. I. Lin, Design and evaluation of bus information at bus stops and printed information brochures for the elderly, Transportation Planning Journal 38(4) (2009) 355–380. Google Scholar
    • 3. J. L. Fan, J. X. Wang, F. Li, H. Yu and X. Zhang, Energy demand and greenhouse gas emissions of urban passenger transport in the Internet era: A case study of Beijing, Journal of Cleaner Production 165 (2017) 177–189. Crossref, Web of Science, Google Scholar
    • 4. F. Al-Turjman, GHetNet: A framework validating green mobile femtocells in smart-grids, Transportation and Power Grid in Smart Cities: Communication Networks and Services (2018) 191–216. Crossref, Google Scholar
    • 5. R. Chaudhary, A. Jindal, G. S. Aujla, S. Aggarwal, N. Kumar and K. K. R. Choo, BEST: Blockchain-based secure energy trading in SDN-enabled intelligent transportation system, Computers & Security 85 (2019) 288–299. Crossref, Web of Science, Google Scholar
    • 6. M. Abbasi, M. Yaghoobikia, M. Rafiee, A. Jolfaei and M. R. Khosravi, Energy-efficient workload allocation in fog-cloud based services of intelligent transportation systems using a learning classifier system, IET Intelligent Transport Systems 14(11) (2020) 1484–1490. Crossref, Web of Science, Google Scholar
    • 7. Y. Cao, N. Ahmad, O. Kaiwartya, G. Puturs and M. Khalid, Intelligent transportation systems enabled ICT framework for electric vehicle charging in smart city, in Handbook of Smart Cities (Springer, Cham, 2018), pp. 311–330. Google Scholar
    • 8. S. Saharan, S. Bawa and N. Kumar, Dynamic pricing techniques for intelligent transportation system in smart cities: A systematic review, Computer Communications 150 (2020) 603–625. Crossref, Web of Science, Google Scholar
    • 9. G. S. Aujla, A. Jindal and N. Kumar, EVaaS: Electric vehicle-as-a-service for energy trading in SDN-enabled smart transportation system, Computer Networks 143 (2018) 247–262. Crossref, Web of Science, Google Scholar
    • 10. J. Sedlmeir, H. U. Buhl, G. Fridgen and R. Keller, The energy consumption of blockchain technology: Beyond myth, Business & Information Systems Engineering 62(6) (2020) 599–608. Crossref, Web of Science, Google Scholar
    • 11. V. Chauhan, M. Patel, S. Tanwar, S. Tyagi and N. Kumar, Iot enabled real-time urban transport management system, Computers & Electrical Engineering 86 (2020) 106746. Crossref, Web of Science, Google Scholar
    • 12. R. M. Rizk-Allah, A. E. Hassanien and M. Elhoseny, A multi-objective transportation model under neutrosophic environment, Computers & Electrical Engineering 69 (2018) 705–719. Crossref, Web of Science, Google Scholar
    • 13. T. Gaber, S. Abdelwahab, M. Elhoseny and A. E. Hassanien, Trust-based secure clustering in WSN-based intelligent transportation systems, Computer Networks 146 (2018) 151–158. Crossref, Web of Science, Google Scholar
    • 14. J. Truby, Decarbonizing Bitcoin: Law and policy choices for reducing the energy consumption of Blockchain technologies and digital currencies, Energy Research & Social Science 44 (2018) 399–410. Crossref, Web of Science, Google Scholar
    • 15. V. E. Sathishkumar, J. Park and Y. Cho, Seoul bike trip duration prediction using data mining techniques, IET Intelligent Transport Systems 14(11) (2020) 1465–1474. Crossref, Web of Science, Google Scholar
    • 16. X. Lu, Z. Guan, X. Zhou, X. Du, L. Wu and M. Guizani, A secure and efficient renewable energy trading scheme based on blockchain in smart grid, in 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS) (IEEE, 2019), pp. 1839–1844. Crossref, Google Scholar
    • 17. M. J. Ashley and M. S. Johnson, Establishing a secure, transparent, and autonomous blockchain of custody for renewable energy credits and carbon credits, IEEE Engineering Management Review 46(4) (2018) 100–102. Crossref, Google Scholar
    • 18. B. Esmaeilian, J. Sarkis, K. Lewis and S. Behdad, Blockchain for the future of sustainable supply chain management in Industry 4.0, Resources, Conservation and Recycling 163 (2020) 105064. Crossref, Web of Science, Google Scholar
    • 19. A. Lei, H. Cruickshank, Y. Cao, P. Asuquo, C. P. A. Ogah and Z. Sun, Blockchain-based dynamic key management for heterogeneous intelligent transportation systems, IEEE Internet of Things Journal 4(6) (2017) 1832–1843. Crossref, Web of Science, Google Scholar
    • 20. R. Chaudhary, A. Jindal, G. S. Aujla, S. Aggarwal, N. Kumar and K. K. R. Choo, BEST: Blockchain-based secure energy trading in SDN-enabled intelligent transportation system, Computers & Security 85 (2019) 288–299. Crossref, Web of Science, Google Scholar
    • 21. L. A. Hîrţan, C. Dobre and H. González-Vélez, Blockchain-based reputation for intelligent transportation systems, Sensors 20(3) (2020) 791. Crossref, Web of Science, Google Scholar
    • 22. K. K. Bhardwaj, A. Khanna, D. K. Sharma and A. Chhabra, Designing energy-efficient IoT-based intelligent transport system: need, architecture, characteristics, challenges, and applications, in Energy Conservation for IoT Devices (Springer, Singapore, 2019), pp. 209–233. Crossref, Google Scholar
    • 23. C. Yang, M. Zha, W. Wang, K. Liu and C. Xiang, Efficient energy management strategy for hybrid electric vehicles/plug-in hybrid electric vehicles: review and recent advances under intelligent transportation system, IET Intelligent Transport Systems 14(7) (2020) 702–711. Crossref, Web of Science, Google Scholar
    • 24. A. Jindal, G. S. Aujla and N. Kumar, SURVIVOR: A blockchain based edge-as-a-service framework for secure energy trading in SDN-enabled vehicle-to-grid environment, Computer Networks 153 (2019) 36–48. Crossref, Web of Science, Google Scholar
    • 25. Y. Wang, Z. Su and N. Zhang, BSIS: Blockchain-based secure incentive scheme for energy delivery in vehicular energy network, IEEE Transactions on Industrial Informatics 15(6) (2019) 3620–3631. Crossref, Web of Science, Google Scholar
    • 26. H. Fatemidokht, M. K. Rafsanjani, B. B. Gupta and C. H. Hsu, Efficient and secure routing protocol based on artificial intelligence algorithms with UAV-assisted for vehicular Ad Hoc networks in intelligent transportation systems, IEEE Transactions on Intelligent Transportation Systems (2021). Crossref, Web of Science, Google Scholar
    • 27. Q. Yang, H. Wang, T. Wang, S. Zhang, X. Wu and H. Wang, Blockchain-based decentralized energy management platform for residential distributed energy resources in a virtual power plant, Applied Energy 294 (2021) 117026. Crossref, Web of Science, Google Scholar
    • 28. Y. C. Tsao and V. V. Thanh, Toward blockchain-based renewable energy microgrid design considering default risk and demand uncertainty, Renewable Energy 163 (2021) 870–881. Crossref, Web of Science, Google Scholar
    • 29. A. Hasankhani, S. M. Hakimi, M. Shafie-Khah and H. Asadolahi, Blockchain technology in the future smart grids: A comprehensive review and frameworks, International Journal of Electrical Power & Energy Systems 129 (2021) 106811 Crossref, Web of Science, Google Scholar
    • 30. C. Esposito, M. Ficco and B. B. Gupta, Blockchain-based authentication and authorization for smart city applications, Information Processing & Management 58(2) (2021) 102468. Crossref, Web of Science, Google Scholar
    • 31. B. B. Gupta, K. C. Li, V. C. Leung, K. E. Psannis and S. Yamaguchi, Blockchain-assisted secure fine-grained searchable encryption for a cloud-based healthcare cyber-physical system, IEEE/CAA Journal of Automatica Sinica (2021). Web of Science, Google Scholar
    • 32. G. N. Nguyen, N. H. Le Viet, M. Elhoseny, K. Shankar, B. B. Gupta and A. A. Abd El-Latif, Secure blockchain enabled cyber–physical systems in healthcare using deep belief network with ResNet model, J. Parallel and Distributed Computing 153 (2021) 150–160. Crossref, Web of Science, Google Scholar