Skip to main content

Advertisement

SpringerLink
Log in

Threshold Based Efficient Road Monitoring System Using Crowdsourcing Approach

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

This paper describes a road monitoring system using crowdsourcing approach to locate potholes and speed breakers. The continuous monitoring of the real-time road anomalies allows acceptable infrastructure maintenance and management operation. For this purpose, a system has been described and different methods have been presented to monitor the conditions of the roads. The suggested system has a driver-friendly interface, demanding neither driver assisted training processes, nor complicated installation and thus it is conceivable to attain hassle-free mass deployment such that drivers would be willing to participate in crowdsourcing. Testing of the system is performed on hundreds of kilometers and it successfully locates the number of road anomalies. To find the accuracy of the proposed system dedicated sensors were installed on the vehicles. Furthermore, by comparing the results of both smartphone and dedicated sensors, it showed that the system reported 90% of the real road anomalies. Not only the system reports the presence of road anomalies, however, it also categorizes different types of potholes and speed breakers by analyzing depth, width and severity of anomalies. After the segregation of different types of anomalies, they are marked on to the map by using pointers of different colours. Along with addition of markers the system is efficient enough to remove the markers if a particular obstacle is repaired by the authorities. In addition, the system calculates the international roughness index of the roads as well.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

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

References

  1. Allamehzadeh, A., de la Parra, J. U., Hussein, A., Garcia, F., & Olaverri-Monreal, C. (2017). Cost-efficient driver state and road conditions monitoring system for conditional automation. In 2017 IEEE intelligent vehicles symposium (IV) (pp. 1497–1502). IEEE.

  2. Apostoloff, N., & Zelinsky, A. (2004). Vision in and out of vehicles: Integrated driver and road scene monitoring. The International Journal of Robotics Research, 23(4–5), 513–538.

    Article  Google Scholar 

  3. Carrera, F., Guerin, S., & Thorp, J. (2013). By the people, for the people: The crowdsourcing of streetbump—An automatic pothole mapping app. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 40, 19–23.

    Article  Google Scholar 

  4. Chen, K., Lu, M., Fan, X., Wei, M., & Wu, J. (2011). Road condition monitoring using on-board three-axis accelerometer and GPS sensor. In 2011 6th International ICST conference on communications and networking in China (CHINACOM) (pp. 1032–1037). IEEE.

  5. Chen, K., Tan, G., Lu, M., & Wu, J. (2016). CRSM: A practical crowdsourcing-based road surface monitoring system. Wireless Networks, 22(3), 765–779.

    Article  Google Scholar 

  6. Eriksson, J., Girod, L., Hull, B., Newton, R., Madden, S., & Balakrishnan, H. (2008). The pothole patrol: Using a mobile sensor network for road surface monitoring. In Proceedings of the 6th international conference on Mobile systems, applications, and services (pp. 29–39). ACM.

  7. Ghose, A., Biswas, P., Bhaumik, C., Sharma, M., Pal, A., & Jha, A. (2012). Road condition monitoring and alert application: Using in-vehicle smartphone as internet-connected sensor. In 2012 IEEE international conference on pervasive computing and communications workshops (pp. 489–491). IEEE.

  8. Gondal, I., Yaqub, M. F., & Hua, X. (2012). Smart phone based machine condition monitoring system. In International conference on neural information processing (pp. 488–497). Springer.

  9. González-Gurrola, L. C., Martínez-Reyes, F., & Carlos-Loya, M. R. (2013). The citizen road watcher—Identifying roadway surface disruptions based on accelerometer patterns. In Ubiquitous computing and ambient intelligence. Context-awareness and context-driven interaction (pp. 374–377). Springer.

  10. Hull, B., Bychkovsky, V., Zhang, Y., Chen, K., Goraczko, M., Miu, A., Shih, E., Balakrishnan, H., & Madden, S. (2006) CarTel: A distributed mobile sensor computing system. In Proceedings of the 4th international conference on Embedded networked sensor systems (pp. 125–138). ACM.

  11. Ito, K., Hirakawa, G., Arai, Y., & Shibata, Y. (2015). A road condition monitoring system using various sensor data in challenged communication network environment. In 2015 IEEE 29th international conference on advanced information networking and applications workshops (pp. 518–523). IEEE.

  12. Kaur, V., Tyagi, A., Kritika, M., Kumari, P., & Salvi, S. (2017). Crowd-sourcing based android application for structural health monitoring and data analytics of roads using cloud computing. In 2017 International conference on innovative mechanisms for industry applications (ICIMIA) (pp. 354–358). IEEE.

  13. Koukoumidis, E., Martonosi, M., & Peh, L. S. (2012). Leveraging smartphone cameras for collaborative road advisories. IEEE Transactions on Mobile Computing, 11(5), 707–723.

    Article  Google Scholar 

  14. Lima, L. C., Amorim, V. J. P., Pereira, I. M., Ribeiro, F. N., & Oliveira, R. A. R. (2016). Using crowdsourcing techniques and mobile devices for asphaltic pavement quality recognition. In 2016 VI Brazilian symposium on computing systems engineering (SBESC) (pp. 144–149). IEEE.

  15. Limkar, S., Rajmane, O., Bhosale, A., & Rane, V. (2018). Small effort to build Pune as a smart city: Smart real-time road condition detection and efficient management system. In S. Satapathy, V. Bhateja, & S. Das (Eds.), Smart computing and informatics. Smart innovation, systems and technologies (pp. 609–621). Singapore: Springer.

    Chapter  Google Scholar 

  16. Mesin, L., Troiano, A., & Pasero, E. (2010). In field application of an innovative sensor for monitoring road and runway surfaces. In 2010 First international conference on sensor device technologies and applications (pp. 157–161). IEEE.

  17. Mohamed, A., Fouad, M. M. M., Elhariri, E., El-Bendary, N., Zawbaa, H. M., Tahoun, M., & Hassanien, A. E. (2015). Roadmonitor: An intelligent road surface condition monitoring system. In Intelligent systems’ 2014 (pp. 377–387). Springer.

  18. Mukherjee, A., & Majhi, S. (2016). Characterisation of road bumps using smartphones. European Transport Research Review, 8(2), 13.

    Article  Google Scholar 

  19. Nalavde, R., & Surve, A. (2015). Driver assistant services using ubiquitous smartphone. In 2015 International conference on communications and signal processing (ICCSP) (pp. 0430–0434). IEEE.

  20. Organization, W. H. (2018). Road traffic injuries. http://www.who.int/mediacentre/factsheets/fs358/en/. Accessed February 19, 2019.

  21. Perttunen, M., Mazhelis, O., Cong, F., Kauppila, M., Leppänen, T., Kantola, J., Collin, J., Pirttikangas, S., Haverinen, J., & Ristaniemi, T., et al. (2011). Distributed road surface condition monitoring using mobile phones. In International conference on ubiquitous intelligence and computing (pp. 64–78). Springer.

  22. Rishiwal, V., & Khan, H. (2016). Automatic pothole and speed breaker detection using android system. In 2016 39th International convention on information and communication technology, electronics and microelectronics (MIPRO) (pp. 1270–1273). IEEE.

  23. Sathe, A. D., & Deshmukh, V. D. (2016). Advance vehicle-road interaction and vehicle monitoring system using smart phone applications. In 2016 Online international conference on green engineering and technologies (IC-GET) (pp. 1–6). IEEE.

  24. Yakimenko, A., Bogomolov, D., Morozov, A., & Sokolova, A. (2017). Development and research of the information system for monitoring the condition of the road surface using mobile devices to optimize logistics and repair costs. In 2017 International multi-conference on engineering, computer and information sciences (SIBIRCON) (pp. 190–192). IEEE.

  25. Yi, C. W., Chuang, Y. T., & Nian, C. S. (2015). Toward crowdsourcing-based road pavement monitoring by mobile sensing technologies. IEEE Transactions on Intelligent Transportation Systems, 16(4), 1905–1917.

    Article  Google Scholar 

  26. Zan, B., Sun, T., Gruteser, M., & Zhang, Y. (2010) Rome: Road monitoring and alert system through geocache. In 2010 IEEE international symposium on parallel and distributed processing, workshops and Ph.D. forum (IPDPSW) (pp. 1–8). IEEE.

Download references

Acknowledgements

This research work is partially supported by Higher Education Commission Pakistan under the National Center for Robotics and Automation (NCRA) joint lab established at the Mehran University of Engineering and Technology, Jamshoro titled ‘Haptics, Human Robotics and Condition Monitoring Systems’.

Author information

Authors and Affiliations

  1. Department of Telecommunication Engineering, Mehran UET, Jamshoro, Pakistan

    Naveed Sabir, Anzal Ali Memon & Faisal Karim Shaikh

Authors
  1. Naveed Sabir
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anzal Ali Memon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Faisal Karim Shaikh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Faisal Karim Shaikh.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sabir, N., Memon, A.A. & Shaikh, F.K. Threshold Based Efficient Road Monitoring System Using Crowdsourcing Approach. Wireless Pers Commun 106, 2407–2425 (2019). https://doi.org/10.1007/s11277-019-06324-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-019-06324-y

Keywords

Search

Navigation