Call for Paper - March 2023 Edition
IJCA solicits original research papers for the March 2023 Edition. Last date of manuscript submission is February 20, 2023. Read More

An Early Alert System for Traffic Congestion based on Social Messages on Smartphones

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Abdullah Abdullah, Manzoor Ali, Ahmed Hassan

Abdullah Abdullah, Manzoor Ali and Ahmed Hassan. Article: An Early Alert System for Traffic Congestion based on Social Messages on Smartphones. International Journal of Computer Applications 133(11):27-32, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {Abdullah Abdullah and Manzoor Ali and Ahmed Hassan},
	title = {Article: An Early Alert System for Traffic Congestion based on Social Messages on Smartphones},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {133},
	number = {11},
	pages = {27-32},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


Road traffic congestion is a global problem and large amount of money is being invested to cope with traffic congestion problems. These interventions focus on reducing traveler time on roads and highways in particular. Various approaches such as loop detection and automatic vehicle detection have been utilized for this purpose but all these happen to be very costly. The main purpose of this study is to propose a smartphone application through which users can share congestion information through social messages. This application is based on client-server architecture. On the client side, it gives traffic congestion information to the server; while on the reverse side, it takes information from the server and disseminates it to relevant users. A user searches for congestion information shared through social messages on a planned route in order to check if his path is clear or congested. In this way, the user can get timely be informed and thus be able to avoid that congested path and look for alternative routes.


  1. Padiath, A., Vanajakshi, L., Subramanian, S. C., & Manda, H. (2009, October). Prediction of traffic density for congestion analysis under Indian traffic conditions. In Intelligent Transportation Systems, 2009. ITSC'09. 12th International IEEE Conference on (pp. 1-6). IEEE.
  2. Steenbruggen, J., Borzacchiello, M. T., Nijkamp, P., & Scholten, H. (2013). Mobile phone data from GSM networks for traffic parameter and urban spatial pattern assessment: a review of applications and opportunities. GeoJournal,78(2), 223-243.
  3. M.W.H.M. De Silva, K.M.S.M. Konara, I.R.A.I. Karunarathna, K.K.U.P. Lal and M. Wijesundara, “An Information System for Vehicle Navigation in Congested Road Networks”, PNCTM; VOL3, JAN 2014
  6. Wang, J., Qiao, F., & Lu, J. (2013). Research and application of the location information in the intelligent transportation.
  7. Mulay, S., Dhekne, C., Bapat, R., Budukh, T., & Gadgil, S. (2013). Intelligent City Traffic Management and Public Transportation System. arXiv preprint arXiv:1310.5793.
  8. Reza, S. M., Rahman, M., & Mamun, S. A. (2014, April). A new approach for road networks?? A vehicle XML device collaboration with big data. In Electrical Engineering and Information & Communication Technology (ICEEICT), 2014 International Conference on (pp. 1-5). IEEE.
  9. Thiagarajan, A., Ravindranath, L., LaCurts, K., Madden, S., Balakrishnan, H., Toledo, S., & Eriksson, J. (2009, November). VTrack: accurate, energy-aware road traffic delay estimation using mobile phones. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (pp. 85-98). ACM.
  13. http://blog-
  14. Barbeau, S., Labrador, M. A., Perez, A. J., Winters, P. L., Georggi, N. L., Aguilar, D., & Perez, R. A. (2008, September). Dynamic management of real-time location data on GPS-enabled mobile phones. In Mobile Ubiquitous Computing, Systems, Services and Technologies, 2008. UBICOMM'08. The Second International Conference on (pp. 343-348). IEEE.
  16. Sun, Z., Gu, W., Feng, J., & Zhu, X. Threshold Value Based Traffic Congestion Identification Method. entropy, 1,1.


Congestion, traffic, information, smartphone, social messages.