Public transportation is highly cost effective and environmental friendly solution for commuters. But the unreliability of the system because of lack of communication often prevents its widespread use. This paper describes the solution which makes the public Transportation more intelligent. The emphasis of this paper is on prediction of the bus arrival time, distance and geo-location based on various aspects like bus availability, average running speed and bus current location. For analysing these aspects, we have developed range of algorithms like dividing routes into segments, mapping bus location onto segment and finding accurate information for user’s query. Required resources are classified into two modules namely the GPS(Global Positioning System) module for tracking the bus’s potential GPS logs and the network infrastructure that allows the users to communicate, by querying for the bus information and receiving response on different platform like SMS, Android.
Android, Global Positioning System (GPS), Intelligent Transportation System, Travel Time Prediction, Real Time Tracking System, ,Short Messaging Service (SMS).
 Fu, L., and X. Yang. “Design Implementation of Bus-Holding Control Strategies with Real-Time Information.” In Transportation Research Record: Journal of the Transportation Research Board, No. 1791, Transportation Research Board of the National Academies, Washington, D.C. (2002), pp. 6–12.
 Ehsan Mazloumi, Graham Currie, Geoff Rose, and Majid Sarvi. Using SCATS data to predict bus travel time. Institute of Transport Studies, Monash University, Melbourne, Australia
 Jason Dudley, Ron Vetter, Jeff Brown, Tom Janicki. Building a Real-Time Bus Tracking Data Display System. UNC Wilmington, North Carolina 28403 USA.
 Jerald Jariyasunant, Eric Mai, Raja Sengupta. Algorithm for finding optimal paths in a public transit network with real-time data. Department of Civil Engineering, University of California, Berkeley.
 Dihua Sun, Hong Luo, Liping Fu, Weining Liu, Xiaoyong Liao, and Min Zhao. Predicting Bus Arrival Time on the Basis of Global Positioning System Date
 James Biagioni, Tomas Gerlich, Timothy Merrifield, Jakob Eriksson. Easy Tracker: Automatic Transit Tracking, Mapping, and Arrival Time Prediction Using Smartphones. Department of Computer Science, University of Illinois at Chicago, Chicago, IL 60607, USA.
 Schweiger, C. L. TCRP Synthesis 48: “Real-Time Bus Arrival Information Systems: A Synthesis of Transit Practice. Transportation Research”.
 Mr.Y.Ramakrishna,Mr.P.Ramakrishna,Dr.R.Sivanandan, Mr. V.Lakshmanan. System: Bus Travel Time Prediction Using GPS Data.
 Hong-En LIN, rococo ZITO, A Review of Travel-Time Prediction in Transport and Logistics. Record: Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, pp. 1433 - 1448, (2005).
 Google Transit Program (2012) http://maps.google.com/help/maps/transit/partners.
[Swati B Patil , Saroja M. Kulkarni (2014) Real Time Tracking System using GPS IJIRCST Vol-2 Issue-3 Page No-49-52] (ISSN 2347 - 5552). www.ijircst.org
Swati B Patil
Information Technology, University of Pune,Vishwakarma Institute of Information Technology,Maharashtra,India -411047(email: email@example.com)