With the widespread adoption of location tracking technologies like GPS, the domain of intelligent transportation services has seen growing interest in the last few years. Services in this domain make use of real-time location-based data from a variety of sources, combine this data with static location-based data such as maps and points of interest databases, and provide useful information to end-users. Some of the major challenges in this domain include i) scalability, in terms of processing large volumes of real-time and static data; ii) extensibility, in terms of being able to add new kinds of analyses on the data rapidly, and iii) user interaction, in terms of being able to support different kinds of one-time and continuous queries from the end-user. In this talk, I shall demonstrate the use of IBM Infosphere Streams, a scalable stream processing platform, for tackling these challenges. I shall describe a prototype system that generates dynamic, multi-faceted views of transportation information for the city of Stockholm, using real vehicle GPS and road-network data. The system also continuously derives current traffic statistics, and provides useful value-added information such as shortest-time routes from real-time observed and inferred traffic conditions. Our performance experiments illustrate the scalability of the system. For instance, our system can process over 250000 incoming GPS points per second, combine it with a map containing over 600,000 links, continuously generate different kinds of traffic statistics and answer user queries.

Bio: Anand Ranganathan is a Research Staff Member at IBM TJ Watson Research Center. He is part of IBM Infosphere Streams research team and has been involved in applications of stream processing technologies in a variety of Smarter Planet projects, including transportation and energy management. A key theme of his research has been in exploring the knowledge engineering, software engineering and user interaction challenges in developing component-based applications. He finished his PhD at the Department of Computer Science in the University of Illinois at Urbana-Champaign in 2005. He received his BTech in Computer Science and Engineering from the Indian Institute of Technology in Chennai in 2000. His broad research interests include data management, services, Web 2.0, ubiquitous computing, distributed systems, the Semantic Web, artificial intelligence and software engineering.