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A Platform for Location Aware Service with Human Computation, PLASH

Mission-oriented Project. A Platform for Location Aware Service with Human Computation, PLASH. Ling-Jyh Chen, Meng Chang Chen, Sheng-Wei Chen, Jan-Ming Ho, Wang-Chien Lee, Jane Liu, De-Nian Yang. Presenter: Meng Chang Chen. Intelligent & Ubiquitous Computing Center.

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A Platform for Location Aware Service with Human Computation, PLASH

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  1. Mission-oriented Project A Platform for Location Aware Service with Human Computation, PLASH • Ling-Jyh Chen, Meng Chang Chen, Sheng-Wei Chen, Jan-Ming Ho, Wang-Chien Lee, Jane Liu, De-Nian Yang Presenter: Meng Chang Chen

  2. Intelligent & Ubiquitous Computing Center Technical DevelopmentMobile Networking & CommunicationMultimedia Content Management Virtual infrastructure for interactive cloud app. Platforms PLASH Industrial Collaboration +

  3. History of PLASH • Kicked off in August 2009 • Supported by NSC NCP office • Also supported by CITI & IIS • A 3-year project • Personnel • Ling-Jyh Chen, Meng Chang Chen, Sheng-Wei Chen, Jan-Ming Ho, Wang-Chien Lee, Jane Liu, De-Nian Yang • 10 -12 Research Assistants

  4. Goals and Deliveries of PLASH • To provide a platform to allow voluntary users via “human computation games” to contribute their location-based observations/efforts so as to facilitate some difficult location aware tasks. • (Difficult location aware tasks) City profiling (surface traffic estimation, telecommunication network performance monitoring, city trend analysis) trip planning, spot locating, etc. • To explore novel technologies to support the location aware platform and applications. • Massive data mining, location-based query, image-assisting positioning, indoor positioning/tomography

  5. Goals of PLASH (contd.) • To design a layered architecture to allow application builders to conveniently create their systems. • To provide a location-based dataset benchmark for various research • To build and transfer prototype to potential receivers. • To promote the use of wireless communications.

  6. <VID, GPS Position, Time, other info> Scenario 1: traffic estimation and dynamic routing Volunteers send information periodically <VID, GPS Position, Time, other info>

  7. 1. System derives traffic conditions. Jammed Area Jammed Area Green Area Green Area Green Area Green Area Jammed Area 4. Dynamic reroute. 3. Now it is jammed! 2. System derives a route. Original navigation Re-routed navigation

  8. Scenario 2: available parking locating: V2V <Parking Available> <Looking for Park space>

  9. Scenario 2: available parking locating: V2I2V 3G, WiMax Mobile AP (taxi, bus) 802.11g Users (source) Destination Mobile Access Cluster

  10. PLASH Architecture Applications Map N’ Track Itinerary recommendation Friend compass Massive data mining Technologies Fundamental services Literacy Enabling Service Service layer Data layer Data representation, storage and access City Profiling Geo-location query V2I, V2V Localized data assimilation Communication layer

  11. Related Works (1) – Handout

  12. Related Works (2) - Handout

  13. Related Works (3?) - Handout

  14. SWOT Analysis W S O T

  15. Progress of 1st Year • Literacy Enabling Web Service for Location-Aware Systems • Goal: to assist identifying location by using image • Geo-location Query Service • Goal: to provide on-line geo-location query service • Localized Data Dissemination in V2V networks • to develop a localized data dissemination scheme via exploiting the intermittent connectivity of vehicle networks. • Location-related Applications • Map N’Track Friends: let your friend know where your travel route • Itinerary recommendation: provide personalized route • Friend compass: indicate where a friend is

  16. Future Work • Deployand operate the following applications • Track-a-friend: let your friend know where your travel route • Travel route recommendation: provide personalized route • Friend compass: indicate where a friend is • TAF (TO and FRO) • Innovative enabling technologies and applications • Location-aware user experience summarization using comic Maps • Road anomaly detection using smart phones • Moving object clustering • City Profiling • Understanding the service performance of carriers • Surface traffic estimation • Allow volunteers to build their application by using provided APIs on PLASH. Could be SaaS or PaaS.

  17. PLASH Future Architecture Matured application logic becomes a fundamental service APP 1 APP 2 APP n Fundamental services Service layer Data representation, storage and access Data layer Communication layer V2I, V2V

  18. PLASH Future Architecture APP 1 APP 2 APP n Volunteer can use APIs to build and upload new applications External Application Server Standard APIs PLASH Platform APIs • Authentication (login/logout) • Friend relation • Store location data • Query location data • Query Point of Interest • .. • .. • .. • .. • ..

  19. PLASH Future Architecture – Example Volunteer builds an e-coupon service Coupons On the Go Coupon Service Coupon DB Standard APIs PLASH Platform Let me know if my user is within 100 meters nd towards me. Geo-Range query

  20. PLASH Future Architecture – Example Send the user an e-coupon Coupons On the Go Coupon Service Coupon DB Update location data Standard APIs PLASH Platform Geo-Range query Find a user satisfying the range query

  21. PLASH Future Architecture Coupon Service APP 1 APP 2 APP n Real-Time Traffic Hopefully many volunteer services built on PLASH Standard APIs Route Suggestion PLASH Platform Other Location-Based Services

  22. Potential PLASH Receivers • Literacy Enabling Web Service and Comic Summarization • Location-based service providers • Location-based Human Computation Games • Phone manufacturers, telecom carriers • City Profiling • Traffic authority, telecom carriers, map service providers • V2V related technologies • ITS-related industry • PLASH platform • Carriers

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