f An IoT based Traffic Control System using Spatio-Temporal Shape Process for Density Estimation
FOREX Press I. J. of Electrical & Electronics Research
Support Open Access
  • Home/
  • IJEER-120234

Research Article |

An IoT based Traffic Control System using Spatio-Temporal Shape Process for Density Estimation

Author(s): Karthick Rajan*, T. Ganesh Kumar and K. Sampath Kumar

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 12, Issue 2

Publisher : FOREX Publication

Published : 22 June 2024

e-ISSN : 2347-470X

Page(s) : 590-595

DOI: https://doi.org/10.37391/IJEER.120234

Abstract

In response to the escalating challenges posed by urban congestion and road accidents, this paper addresses the imperative for advanced traffic control systems in smart cities. However, there is limited research work available in the literature to develop this traffic management system due to unpredictable traffic flow occurring on the road. To overcome this shortcoming in the traffic control system, this paper proposed a novel vehicle density estimation method that considers group of vehicles, availability and applicability of IoT in smart cities provide an efficient medium to handle public safety by using condition-based intensity function that will be a medium to cope with traffic challenges and thus build an intelligent traffic control system.

Keywords: IoT Traffic Management System, Density Estimation, Sensors, Traffic Control, Accident Detection.




Karthick Rajan*, Research Scholar, School of Computing Science and Engineering, Galgotias University, Gautam Buddh Nagar, Uttar Pradesh, India; Email: karthickcse88@gmail.com

T. Ganesh Kumar, Associate Professor, School of Computer Science and Engineering, Galgotias University, Buddh Nagar, Uttar Pradesh, India

K. Sampath Kumar, Professor, Computer Science and Engineering, AMET University, Chennai 603112, Tamilnadu, India

    [1] WHO, “World Health Statistics 2014: A Wealth of Information of Global Public Health,” Geneva, 2014. [Online]. Available: https://apps.who.int/iris/handle/10665/112739.
    [2] WHO, “Global Status Report on Road Safety 2018: Summary,” Geneva, 2018. [Online]. Available:https://www.who.int/violence_injury_prevention/road_safety_status/20 18/English-Summary-GSRRS2018.pdf.
    [3] E. B. Lerner and R. M. Moscati, “The Golden Hour: Scientific Fact or Medical ‘Urban Legend’?,” Acad. Emerg. Med., 2001.
    [4] R. Sánchez-Mangas, A. García-Ferrrer, A. De Juan, and A. M. Arroyo, “The probability of death in road traffic accidents. How important is a quick medical response?,” Accid. Anal. Prev., 2010.
    [5] M. A. Razzaque, M. Milojevic-Jevric, A. Palade, and S. Cla, “Middleware for internet of things: A survey,” IEEE Internet Things J., 2016.
    [6] G. Ponte, G. A. Ryan, and R. W. G. Anderson, “An estimate of the effectiveness of an in-vehicle automatic collision notification system in reducing road crash fatalities in South Australia,” Traffic Inj. Prev., 2016.
    [7] Y. Chung and W. W. Recker, “A Methodological Approach for Estimating Temporal and Spatial Extent of Delays Caused by Freeway Accidents,” IEEE Trans. Intell. Transp. Syst., 2012.
    [8] M. Asha Paul, J.Kavitha, P.A Rani (2018). “Keyframe extraction techniques: A review”. Recent Patents on Computer Science, 11(1), 3–16.
    [9] F. Bhatti, M. A. Shah, C. Maple, and S. Ul Islam, “A novel internet of things-enabled accident detection and reporting system for smart city environments,” Sensors (Switzerland), 2019.
    [10] Shaik et al., “Smart Car: An IoT Based Accident Detection System,” in 2018 IEEE Global Conference on Internet of Things, GCIoT 2018, 2019.
    [11] S. Sharma and S. Sebastian, “IoT based car accident detection and notification algorithm for general road accidents,” Int. J. Electr. Comput. Eng., 2019.
    [12] E. K. Priya et al., “IoT Based Vehicle Tracking and Accident Detection System,” Int. J. Innov. Res. Comput. Commun. Eng., vol. 5, no. 3, 2017.
    [13] B. K. Dar, M. A. Shah, S. U. Islam, C. Maple, S. Mussadiq, and S. Khan, “Delay-Aware Accident Detection and Response System Using Fog Computing,” IEEE Access, 2019.
    [14] B. Fernandes, M. Alam, V. Gomes, J. Ferreira, and A. Oliveira, “Automatic accident detection with multi-modal alert system implementation for ITS,” Veh. Commun., 2016.
    [15] Rachedi and H. Badis, “BadZak: An Hybrid Architecture Based on Virtual Backbone and Software Defined Network for Internet of Vehicles,” in IEEE International Conference on Communications, 2018.
    [16] T. Mekki, I. Jabri, A. Rachedi, and M. Ben Jemaa, “Vehicular cloud networking: Evolutionary game with reinforcement learning-based access approach,” in International Journal of Bio-Inspired Computation, 2019.
    [17] D. Acharya, V. Kumar, and G. M. Gaddis, “A Mobile System for Detecting and Notifying Vehicle Rollover Events,” in 15th International Conference on Advanced Computing and Communications (ADCOM 2007), Dec. 2007, pp. 268–275.
    [18] H. A. Ibrahim, A. K. Aly, and B. H. Far, “A system for vehicle collision and rollover detection,” in Canadian Conference on Electrical and Computer Engineering, 2016.
    [19] J. Smolka and M. Skublewska-Paszkowska, “A method for collision detection using mobile devices,” in Proceedings - 2016 9th International Conference on Human System Interactions, HSI 2016, 2016.
    [20] S. Sadek, A. Al-Hamadi, B. Michaelis, and U. Sayed, “Real-time automatic traffic accident recognition using HFG,” in Proceedings - International Conference on Pattern Recognition, 2010.
    [21] V.S. Nagmode, An intelligent framework for vehicle traffic monitoring system using IoT 7e10 (2017).
    [22] M.Z. Talukder, S.S. Towqir, A.R. Remon, H.U. Zaman, An IoT based automated traffic control system with real-time update capability, in: 8th International Conference on Computing, Communications and Networking Technologies, 2017.
    [23] Y. Huang, J. Wang, C. Jiang, H. Zhang, V.C.M. Leung, Vehicular network based reliable traffic density estimation, in: IEEE Vehicular Technology Conference, 2016, pp. 1e5, 2016.
    [24] K. Nellore, G.P. Hancke, Traffic Management for Emergency Vehicle Priority Based on Visual Sensing, 2016.
    [25] M.A. Tank, Review on Smart Traffic Control for Emergency Vehicles 112 (7) (2015).
    [26] S.B. Sangamesh, D.H. Sanjay, S. Meghana, M.N. Thippeswamy, Advanced traffic signal control system for emergency vehicles, 3, pp. 1242-1246, 2019.
    [27] J. S. Kim, D. H. Yeom, and Y. H. Joo, “Fast and robust algorithm of tracking multiple moving objects for intelligent video surveillance systems,” IEEE Trans. Consum. Electron., vol. 57, no. 3, pp. 1165–1170, Aug. 2011.
    [28] M. Elhoseny, “Multi-object detection and tracking (MODT) machine learning model for real-time video surveillance systems,” Circuits, Syst., Signal Process., vol. 39, no. 2, pp. 611–630, Feb. 2020.
    [29] T. J. Vennila and V. Balamurugan, "A Rough Set Framework for Multihuman Tracking in Surveillance Video," in IEEE Sensors Journal, vol. 23, no. 8, pp. 8753-8760, 15 April15, 2023, doi: 10.1109/JSEN.2023.3242007.
    [30] T. J. Vennila and V. Balamurugan, "A Stochastic Framework for Keyframe Extraction," 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE), 2020, pp. 1-5, 2020.
    [31] Todd, N., Schoepflin, N., Dailey, D.J.: Dynamic camera calibration of roadside traffic estimation management cameras for vehicle speed. IEEE Trans. Intell. Transp. Syst. 4(2), 90–98 2003.
    [32] Ketao Deng, Anomaly Detection of Highway Vehicle Trajectory under the Internet of Things Converged with 5G Technology, Complexity, Wiley, pp. 1-12, 2021.
    [33] Wang et al., “Spatio–temporal point process for multiple object track ing,” IEEE Trans. Neural Netw. Learn. Syst., early access, Jun. 8, 2020,
    [34] Mohammed Sarrab, Supriya Pulparambil, Medhat Awadalla, “Development of an IoT based real-time traffic monitoring system for city governance,” Elsevier, Global Transition, pp. 230-245, 2020.
    [35] A. Sodagaran, N. Zarei, Z. Azimifar, Intelligent traffic information system a real-time traffic information system on the shiraz bypass, MATEC Web of Conferences 81, 2016.
    [36] T.J. Lomax, Quantifying Congestion (Issue 398), Transportation Research Board, 1997.
    [37] S. Javaid, A. Sufian, S. Pervaiz, M. Tanveer, Smart traffic management system using Internet of Things, in: International Conference on Advanced Commu nication Technology, ICACT, 2018, pp. 393-398, 2018.

Karthick Rajan, T. Ganesh Kumar and K. Sampath Kumar (2024), An IoT based Traffic Control System using Spatio-Temporal Shape Process for Density Estimation. IJEER 12(2), 590-595. DOI: 10.37391/IJEER.120234.