A Review on Crowd Sourcing Geo-Social Related Big Data Approaches as Solution to Transportation Problem

Abstract:

In order to develop an efficient and safe road there are many methods have been implemented to measure the volume of traffic, to evaluate the road safety level and the others. However based on current practices these methods are very costly as well as complicated. In this paper we present the outcomes of the evaluation on several geosocial networks and transportation networks such as Twitter, Google Map and Waze. The evaluations have been done on the architecture, data inputs and outputs. These findings may give an overview on how all these methods work and how the outputs might be used to improve future road planning.

• Periodical: Applied Mechanics and Materials (Volume 663)
• Pages: 622-626
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.663.622
• Online since: October 2014
• Authors: Abdullah Zawawi Mohamed*
• Keywords: Geosocial Networks, Road Planning, Transportation Networks, Twitter for Road Traffic, Waze

References

[1] Information on http: /www. waze. com.

[2] Information on http: /www. foursquare. com.

[3] Information on http: /www. mobli. com.

[4] I. America, Sizing the U.S. and North American Intelligent Transportation Systems Market: Market Data Analysis of its Revenues and Employment, The Intelligent Transportation Society of America, Tech. Rep., (2011).

[5] Information on http: /www. twitter. com.

[6] Sakaki, Takeshi, Yutaka Matsuo, Tadashi Yanagihara, Naiwala P. Chandrasiri, and Kazunari Nawa, Real-time event extraction for driving information from social sensors, In Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), International Conference on IEEE, 2012, pp.221-226.

DOI: 10.1109/cyber.2012.6392557

[7] Tumasjan, Andranik, Timm Oliver Sprenger, Philipp G. Sandner, and Isabell M. Welpe, Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment, ICWSM, 2010, pp.178-185.

DOI: 10.1609/icwsm.v4i1.14009

[8] N. Wanichayapong, P. Wasawat, P. -A. Wasan, and Pimwadee Chaovalit, Social-based traffic information extraction and classification, In ITS Telecommunications (ITST), 11th International Conference on, IEEE, 2011, pp.107-112.

DOI: 10.1109/itst.2011.6060036

[9] Ben Sharon Rose Ben Jacob Singh, K Xu, Real Time Prediction of Road Traffic Condition in London via Twitter and Related Sources, Middlesex University, (2013).

[10] Y.J. Wu, W. Yinhai, and Q. Dalin, A Google-Map-based arterial traffic information system, In Intelligent Transportation Systems Conference (ITSC), IEEE, 2007, pp.968-973.

DOI: 10.1109/itsc.2007.4357678

[11] F. Michael, K. Dima, P. Rami, R. Lior and E. Yuval, Data mining opportunities in geosocial networks for improving road safety, In Electrical & Electronics Engineers in Israel (IEEEI), 27th Convention of IEEE, 2012, pp.1-4.

DOI: 10.1109/eeei.2012.6377049