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Taxi IQueue
Taxi IQueue
Taxi IQueue
Taxi IQueue
Taxi IQueue
Taxi IQueue
Taxi IQueue
Taxi IQueue
Taxi IQueue
Taxi IQueue
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Taxi IQueue

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This presentation is for a product of Team Albatross for the code::xtremeapps 2011 competition held between 22-23 July 2011 in Singapore. …

This presentation is for a product of Team Albatross for the code::xtremeapps 2011 competition held between 22-23 July 2011 in Singapore.

Over a 24-hour period, we developed a supply/demand informatics system for taxis.

The frontends were developed using OpenCV, Android, and modern HTML5 techniques.

The backend was done using a combination of Django, PostGIS, and Kaazing JMS servers to display taxi stand data in realtime with minimal bandwidth utilization.

This presentation was given to the final judging panel on 25th July 2011, 9:30AM. We were given 15 minutes.

Team Albatross is Li Xuchun, Liu Xiaohui, George Goh.

Blog for this at http://georgegoh.posterous.com/62586121

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  • 1. Taxi IQueue A demand-based recommendation system for cabs Team Albatross 25 July 2011Monday, July 25, 2011
  • 2. Pain Taxi Queues ✤ Not all queues are equal ✤ Queues change Consequence ✤ Taxis and their operators: • Which taxi stand nearby should I go to? • Where is the demand? ✤ Passengers: • Which taxi stand nearby should I go to? • Where can I find the shortest queue? Same Questions Different Objectives+GoalsMonday, July 25, 2011
  • 3. Let’s help people Passengers and taxi drivers see queue lengths: • In real-time • In relation to their location • With an uncomplicated visual interface • With detailed info available The value of enabling informed, real- time decisions: • Taxi drivers make efficient use of time and fuel • Passengers choose which queue is best for them • Datapoints for agility in improving traffic flowMonday, July 25, 2011
  • 4. Doing it like no one else • Computer vision • Real-time face detection using OpenCV • Installed at taxi stands to estimate queue length • Automatic - does not require check-ins or other voluntary passenger interactionMonday, July 25, 2011
  • 5. This is how we do itMonday, July 25, 2011
  • 6. Technologies • OpenCV, native app > Face detection and count • Mobile HTML /JavaScript App > Nearby Queue length display • WebSockets/ /STOMP > Near real-time update of queue length using the JMS gateway. • + + + backend > handling location-aware operationsMonday, July 25, 2011
  • 7. DemoMonday, July 25, 2011
  • 8. Oh, the possibilities! Frontend: Display • Factor in the number of taxis already there • Fuzzy logic instead of numeric displays for queue length Backend: Data analytics • Find previously unknown hotspots • Map demand over time to locationsMonday, July 25, 2011
  • 9. Summary • Problem: Which taxi stand should I go to? • We propose: Mobile visualization of taxi queue lengths, in real-time, without requiring passenger check-ins. • Enabling technologies: Computer vision, Modern mobile devices, Upcoming web standards. • Value: Real-time agility, Supply-demand visualization and data collection, Passenger/taxi decision enablement. • Scope for future work and applications: EnormousMonday, July 25, 2011
  • 10. Thank you Team Albatross Li Xuchun: Specialist(Computer vision, cloud computing) Liu Xiaohui: Engineer(Web, Cloud, HPC, AI) @georgegoh: Programmer(Mobile, Cloud, *args)Monday, July 25, 2011

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