IoV based intelligent vehicle tracker using FoG computing with supervised machine learning techniques

References

• Intyaz Alam & Sushil Kumar (2021) Functionality, privacy, security and rewarding based on fog assisted cloud computing techniques in Internet of Vehicles, Journal of Discrete Mathematical Sciences and Cryptography, DOI: https://doi.org/10.1080/09720529.2020.1794516
   Google Scholar
• Gopal Singh Rawat & Karan Singh (2019) Beacon inter-reception time based adaptive beaconing (BIRA) for congestion-aware vehicular networks, Journal of Discrete Mathematical Sciences and Cryptography, 22:8, 1477-1487, DOI: https://doi.org/10.1080/09720529.2019.1695899
   Web of Science ®Google Scholar
• Sushil Kumar, Upasana Dohare et al. “Cybersecurity Measures for Geocasting in Vehicular Cyber Physical System Environments,”, IEEE Internet of Things Journal, vol. 6, issue 4, pp. 5916–5926, Aug. 2019. doi: https://doi.org/10.1109/JIOT.2018.2872474
   Google Scholar
• Ramesh C. Poonia (2018) Integration of traffic and network simulators for vehicular ad-hoc networks, Journal of Information and Optimization Sciences, 39:7, 1583-1589, DOI: https://doi.org/10.1080/02522667.2017.1406580
   Web of Science ®Google Scholar
• Reena Kasana, Sushil Kumar et al., “Fuzzy-Based Channel Selection for Location Oriented Services in Multichannel VCPS Environments,” IEEE Internet of Things Journal, vol. 5, no. 6, pp. 4642-4651, Dec. 2018. doi: https://doi.org/10.1109/JIOT.2018.2796639
   Google Scholar
• Pratibha Kamal & Nanhay Singh (2020) A new approach buffer-efficient disruption tolerant protocol in vehicular delay-tolerant network, Journal of Information and Optimization Sciences, 41:6, 1395-1405, DOI: https://doi.org/10.1080/02522667.2020.1809094
   Web of Science ®Google Scholar
• Babu Ram & Neelendra Badal (2019) Latency estimation based routing (LEBR) protocol in vehicular adhoc networks (VANETs), Journal of Discrete Mathematical Sciences and Cryptography, 22:8, 1517-1531, DOI: https://doi.org/10.1080/09720529.2019.1700923
   Web of Science ®Google Scholar
• Manish Kumar, Vanita Jain, Achin Jain, Uttam Singh Bisht & Neha Gupta (2019) Evaluation of black hole attack with avoidance scheme using AODV protocol in VANET, Journal of Discrete Mathematical Sciences and Cryptography, 22:2, 277-291, DOI: https://doi.org/10.1080/09720529.2019.1585635
   Web of Science ®Google Scholar
• Bhawna Chaudhary & Karan Singh (2019) Pseudonym generation using genetic algorithm in vehicular ad hoc networks, Journal of Discrete Mathematical Sciences and Cryptography, 22:4, 661-677, DOI: https://doi.org/10.1080/09720529.2019.1642625
   Web of Science ®Google Scholar
• Pratibha Kamal & Nanhay Singh (2020) A new approach buffer-efficient disruption tolerant protocol in vehicular delay-tolerant network, Journal of Information and Optimization Sciences, 41:6, 1395-1405, DOI: https://doi.org/10.1080/02522667.2020.1809094
   Web of Science ®Google Scholar
• O. Kaiwartya, Yue Cao, Jaime Lloret, Sushil Kumar et al., “Geometry-Based Localization for GPS Outage in Vehicular Cyber Physical Systems,” IEEE Transactions on Vehicular Technology, vol. 67, no. 5, pp. 3800-3812, May 2018 doi: https://doi.org/10.1109/TVT.2018.2796242
   Google Scholar
• Ankit Kumar, Pankaj Dadheech, Rajani Kumari & Vijander Singh (2019) An enhanced energy efficient routing protocol for VANET using special cross over in genetic algorithm, Journal of Statistics and Management Systems, 22:7, 1349-1364, DOI: https://doi.org/10.1080/09720510.2019.1618519
   Web of Science ®Google Scholar
• J. He, J. Wei, K. Chen, et al., “Multitier fog computing with large-scale IoT data analytics for smart cities,” IEEE Internet of Things Journal, vol. 4, no. 2, pp. 677-686, 2018. doi: https://doi.org/10.1109/JIOT.2017.2724845
   Google Scholar
• L. Gao, T. H. Luan, S. Yu, et al., “Fog Route: DTN-based data dissemination model in fog computing,” IEEE Internet of Things, Journal, vol. 4, no. 1, pp. 225-235, 2017.
   Web of Science ®Google Scholar
• X. Hou, B. Lin, R. He, et al., “Infrastructure planning and topology optimization for reliable mobile big data transmission under cloud radio access networks,” in EURASIP Journal on Wireless Communicationsand Networking, 2016 (119), pp. 1-11.
   Google Scholar
• H. Hartenstein and K. Laberteaux, VANET: Vehicular Applications and Inter-Networking Technologies, vol. 1, John Wiley & Sons, 2009.
   Google Scholar
• Y. R. B. Al-Mayouf, N. F. Abdullah, M. Ismail, A. W. A. Wahab, and O. A. Mahdi, “Efficient routing algorithm for VANETsbased on distance factor,” in Proceedings of the 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016, pp. 567–571, mys, November 2016.
   Google Scholar
• Y. Sun, R. Lu, X. Lin, X. Shen, and J. Su, “An efficient pseudonymous authentication scheme with strong privacy preservation for vehicular communications,” IEEE Transactions on Vehicular Technology, vol. 59, no. 7, pp. 3589–3603, 2010. doi: https://doi.org/10.1109/TVT.2010.2051468
   Web of Science ®Google Scholar
• Y. R. B. Al-Mayouf, M. Ismail, N. F. Abdullah, S. M. AlQaraawi, and O. A. Mahdi, “Survey on VANET technologies and simulation models,” ARPN Journal of Engineering and Applied Sciences, vol. 11, no. 15, pp. 9414–9427, 2016.
   Google Scholar
• M. Wang, H. Liang, R. Zhang, R. Deng, and X. Shen, “Mobilityaware coordinated charging for electric vehicles in VANETenhanced smart grid,” IEEE Journal on Selected Areas in Communications, vol. 32, no. 7, pp. 1344–1360, 2014. doi: https://doi.org/10.1109/JSAC.2014.2332078
   Web of Science ®Google Scholar
• I. Leontiadis, G. Marfia, D. Mack, G. Pau, C. Mascolo, and M. Gerla, “On the effectiveness of an opportunistic traffic management system for vehicular networks,” IEEE Transactions on Intelligent Transportation Systems, vol. 12, no. 4, pp. 1537–1548, 2011. doi: https://doi.org/10.1109/TITS.2011.2161469
   Web of Science ®Google Scholar
• Ghosh, A.; Chatterjee, T.; Samanta, S.; Aich, J.; Roy, S. Distracted Driving: A Novel Approach towardsAccident Prevention. Adv. Comput. Sci. Technol. 2017, 10, 2693–2705.
   Google Scholar
• Liu, W.; Kim, S.W.; Marczuk, K.; Ang, M.H. Vehicle motion intention reasoning using cooperative perceptionon urban road. In Proceedings of the 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), Qingdao, China, 8–11 October 2014; pp. 424–430.
   Google Scholar
• Devi, S.; Neetha, T. Machine Learning based traffic congestion prediction in a IoT based Smart City. Int. Res.J. Eng. Technol. 2017, 4, 3442–3445.
   Google Scholar
• Munoz-Organero, M.; Ruiz-Blaquez, R.; Sánchez-Fernández, L. Automatic detection of traffic lights, streetcrossings and urban roundabouts combining outlier detection and deep learning classification techniquesbased on GPS traces while driving. Comput. Environ. Urban Syst. 2018, 68, 1–8. doi: https://doi.org/10.1016/j.compenvurbsys.2017.09.005
   Web of Science ®Google Scholar
• Ba, J.; Mnih, V.; Kavukcuoglu, K. Multiple object recognition with visual attention. arXiv2014,arXiv:1412.7755
   Google Scholar
• Ryder, B.; Wortmann, F. Autonomously detecting and classifying traffic accident hotspots. In Proceedingsof the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2017 ACM International Symposium on Wearable Computers, Maui, HI, USA, 11–15 September 2017; pp. 365–370
   Google Scholar