[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Springer Nature Link
Log in

An Efficient Monitoring of Real Time Traffic Clearance for an Emergency Service Vehicle Using IOT

  • Published:
International Journal of Parallel Programming Aims and scope Submit manuscript

Abstract

In this paper, a real time emergency vehicle tracking through architecture of instinctive emergency recognition system with high-intensity digital camera it is located in a national high way traffic signal. In a recent survey, there are thousands of people losing their lives due to the delay in the emergency services. Resent survey say that more than 4000 heart attack victims can be saved each year if the delay could be minimized and in the present scenario the number of deaths is in lakhs and this number can be effectively reduced by providing timely and accurate emergency service all the way through avoiding the unnecessary time delay near traffic jams during an emergency situation (Tagne et al. in IEEE Trans Intell Transp Syst 17(3):796–809, 2015). This method clarifies the modeling and working of different units of the emergency vehicle identification system such that optimized emergency vehicle tracking algorithm, with the traffic supervision unit. In this article confer the basic components and their function such that internet of things and their dissimilar layers of protocol, raspberry pi and its architecture, with interfacing sensors such as Siren sound detect (REES-52), the Wireless sensor (NRF905se). It is direct and the most efficient route that is asphalt construct to the central server checks for the location of the vehicle and change the traffic signal. When the emergency vehicle is approaching the traffic lights. The system generate in sequence regarding the traffic emergency situations such as ambulance and siren sound (Emergency Services Review: A comparative review of international ambulance service best practice. http://www.aace.org.uk. Accessed 28 July 2017, 2017). The processed information can be used to divert the live traffic as desirable to avoid the problems related to real time road traffic (Sundar et al. in Sens J IEEE 15(2):1109–1113, 2015).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Tagne, G., Talj, R., Charara, A.: Design and comparison of robust nonlinear controllers for the lateral dynamics of intelligent vehicles. IEEE Trans. Intell. Transp. Syst. 17(3), 796–809 (2015)

    Article  Google Scholar 

  2. Emergency Services Review: A comparative review of international Ambulance Service best practice. http://www.aace.org.uk. Accessed 28 July 2017 (2017)

  3. Sundar, R., Hebbar, S., Golla, V.: Implementing intelligent traffic control systemfor congestion control537 ambulance clearance and stolen vehicle detection. Sens. J. IEEE 15(2), 1109–1113 (2015)

    Article  Google Scholar 

  4. Rahman, A.H.A., et al.: Model based detection and tracking of single moving object using laser range finder. In: Fifth International Conference on Intelligent Systems, Modelling and Simulation (ISMS) (2014)

  5. Küçükoğlu, İ., Öztürk, N.: An advanced hybrid meta-heuristic algorithm for the vehicle routing problem with backhauls and time windows. Comput. Ind. Eng. 86, 60–68 (2015)

    Article  Google Scholar 

  6. Tak, S., Woo, S., Yeo, H.: Study on the framework of hybrid collision warning system using loop detectors and vehicle information. Transp. Res. C Emerg. Technol. 73, 202–218 (2016)

    Article  Google Scholar 

  7. Sireesha, E., Rakesh, D.: Intelligent traffic light system to prioritized emergency purpose vehicles based on wireless sensor network. Int. J. Res. Stud. Sci. Eng. Technol. 1, 24–27 (2014)

    Google Scholar 

  8. Reshma, R., Ramesh, T.K.: Security incident management in ground transportation system using UAVs. IEEE, 978-1-4799-7849-6/15/$31.00 ©2015 IEEE

  9. Ruhnau, P., Vogler, A.: Camera system. In: Particular for a Vehicle, and Method for Ascertaining Pieces of Image Information of a Detection Area. Patent No. US 9,720,148 B2, 1 Aug 2017

  10. Erol, M.H., Bulut, F.: Real-time application of travelling salesman problem using Google Maps API. In: Electric Electronics, Computer Science, Biomedical Engineerings’ Meeting (EBBT), 2017. IEEE (2017)

  11. Cui, H., Liu, W., et al.: School of Automation, Hangzhou Dianzi University, Zhejiang 310018, China. “A hypersonic vehicle tracking algorithm based on the UKF generalized labeled multi-Bernoulli filter”. Accession Number: 16265337, IEEE Conference, 27–29 July (2016)

  12. Yang, H., Rakha, H., Ala, M.V.: Eco-cooperative adaptive cruise control at signalized intersections considering queue effects. IEEE Trans. Intell. Transp. Syst. 18(6), 1–11 (2016)

    Article  Google Scholar 

  13. Kassir, M.M., Palhang, M.: A region based CAM shift tracking with a moving camera. In: Proceeding of the 2nd RSI/ISM International Conference on Robotics and Mechatronics, 15–17 October (2014)

  14. Zargayouna, M., Balbo, F., Ndiaye, K.: Generic model for resource allocation in transportation application to urban parking management. Transp. Res. C Emerg. Technol. 71, 538–554 (2016)

    Article  Google Scholar 

  15. Lee, S.J., Tewolde, G., Kwon, J.: Design and implementation of vehicle tracking system using GPS/GSM/GPRS technology and smartphone application. In: 2014 IEEE World Forum on Internet of Things (WiF-IoT), pp. 353–358, 6–8 March (2014)

  16. Tarapiah, S., Atalla, S., Alsayid, B.: Smart on-board transportation management system geo-casting featured. In: World Congress on Computer Applications and Information Systems (WCCAIS), pp. 1–6, 17–19 Jan (2014)

  17. Fogue, M., et al.: A system for automatic notification and severity estimation of automotive accidents. IEEE Trans. Mob. Comput. 13(5), 948–963 (2014)

    Article  Google Scholar 

  18. Krishna, A.S., Asif Hussain, S.: Smart vehicle security and defending against collaborative attacks by malware. Int. J. Eng. Sci. Comput. (2015). https://doi.org/10.4010/2015.444

    Article  Google Scholar 

  19. Yuan, Y., Xiong, Z., Wang, Q.: An incremental framework for video-based traffic sign detection tracking and recognition. IEEE Trans. Intell. Transp. Syst. 18(7), 1918–1929 (2017)

    Article  Google Scholar 

  20. Qin, J., Ye, Y.: The emergency vehicle routing problem with uncertain demand under sustainability environments. Open Access Sustain. 9(2), 288 (2017). https://doi.org/10.3390/su9020288

    Article  Google Scholar 

  21. Wang, X., Xu, L., Sun, H., Xin, J.M., Zheng, N.: On-road vehicle detection and tracking using MMW radar and monovision fusion. IEEE Trans. Intell. Transp. Syst. 17(7), 2075–2084 (2016)

    Article  Google Scholar 

  22. Kim, Y.-J., Hong, J.-S.: Urban traffic flow prediction system using a multifactor pattern recognition model. IEEE Trans. Intell. Transp. Syst. 16(5), 2744–2755 (2015)

    Article  Google Scholar 

  23. Kaur, H., Sahni, V., Bala, M.: Survey of reactive and hybrid routing protocols in MANET: a review IJCSIT. Int. J. Comput. Sci. Inf. Technol. 4(3), 498–500 (2013)

    Google Scholar 

  24. Isaloo, M., Azimifar, Z.: Anomaly detection on traffic videos based on trajectory simplification. In: IEEE 8th Iranian Conference on Machine Vision and Image Processing (MVIP), pp. 200–203 (2013)

  25. Satzoda, R.K., Trivedi, M.M.: Multipart vehicle detection using symmetry-derived analysis and active learning. IEEE Trans. Intell. Transp. Syst. 17(4), 926–937 (2016)

    Article  Google Scholar 

  26. Zhou, P., Zheng, Y., Li, M.: Predicting bus arrival time with mobile phone based participatory sensing. IEEE Trans. Mob. Comput. 13(6), 1228–1241 (2014)

    Article  Google Scholar 

  27. Thupalli, N.K.: Microphone Array System for Speech Enhancement in Laptop’s. Blekinge Tekniska Högskola, Karlskrona (2012)

    Google Scholar 

  28. Permananda, B.S., Uma, B.V.: Speech enhancement algorithm to reduce the effect of background noise in mobile phones. Int. J. Wirel. Mobile Netw. 5(1), 177 (2013)

    Article  Google Scholar 

  29. Hebbar, S., Pattar, P., Golla, V.: A mobile zigbee module in a traffic control system. Potentials IEEE 35(1), 19–23 (2016)

    Article  Google Scholar 

  30. Thirukrishna, J.T., Karthick, S., Arunachalam, V.P.: Revamp energy efficiency in homogeneous wireless sensor networks using optimized radio energy algorithms and power-aware distance source routing protocol. Future Gener. Comput. Syst. 81, 331–339 (2018). https://doi.org/10.1016/j.future.2017.11.042

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, JIT, Coimbatore, India

    P. Gowtham

  2. Department of Computer Science Engineering, SNSCT, Coimbatore, India

    V. P. Arunachalam, V. A. Vijayakumar & S. Karthik

Authors
  1. P. Gowtham
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. P. Arunachalam
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. V. A. Vijayakumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. S. Karthik
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P. Gowtham.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gowtham, P., Arunachalam, V.P., Vijayakumar, V.A. et al. An Efficient Monitoring of Real Time Traffic Clearance for an Emergency Service Vehicle Using IOT. Int J Parallel Prog 48, 786–812 (2020). https://doi.org/10.1007/s10766-018-0603-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10766-018-0603-9

Keywords

Search

Navigation