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A Community Platform for Auto-Annotated Recreational Maps

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A Community Platform for Auto-Annotated Recreational Maps

  1. 1. A Community Platform forAuto-Annotated Recreational Maps Till Riedel1, Phillip Scholl1, Christian Decker1 and Michael Beigl2 1TecO,Universität Karlsruhe(TH), Vincenz Prießnitz Str. 3 76131 Karlsruhe, Germany <{riedel,scholl,cdecker}@teco.edu> 2IBR,UniversitätBraunschweig, Mühlenpfordstr. 23 Braunschweig , Germany <beigl@teco.edu>
  2. 2. Motivation  Recreational maps  Outdating  Specialized City map Karlsruhe: Skate map Karlsruhe: still using Version from 1990 Specialized Annotation (or Google maps :-) ) Should have newest version !2 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)
  3. 3. Recreational Maps  Specialized for sport, degree of expertise  more detailed annotation = better map  road size doesnt matter  Road quality reflected in coloring/style  Not many print runs depending on sport  Out-dating rapidly: Nature Minor road work3 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)
  4. 4. Alternative: Track sharing communities  Large Community  Sharing single tracks  Simple or text based annotation  Subjective/Biased4 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)
  5. 5. Problem  Track fusion dependent on sports device  Differentiated annotation makes system complex  Users tend not to waste their time on intricate stuff  We need many users to build complete maps Dilemma: many users vs complex system complete maps vs differentiated annotation5 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)
  6. 6. Community Platform for Auto-Annotated Recreational Maps  Minimal effort Automate process as much as possible  Minimal cost Use available technology  Minimal risk Anonymization: dont share raw personal data6 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)
  7. 7. (kind of) Wireless Sensor Networks  Sensor Nodes = Sportsmen w/: Sensor Watches/Sensors on Equipment Handheld GPS Systems  Mobile sparsely synchronized sensors high coverage high availabiliy only back-end communication7 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)
  8. 8. Track Classification  Classifier for Road Quality  Use input from sensors: Acceleration Vibration GPS (speed, slope)  Simple rule based system: e.g.: low(vibration(R)) => good(R) Preset rule sets for different devices/preferences Adjustable by user8 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)
  9. 9. Map Creation  Create network of roads  Which tracks belong to same road? Routes not equal in strict sense  Algorithm described in: Scott Morris, Alan Morris, Kobus Barnard, Digital Trail Libraries, jcdl, pp. 63-71, Digital Libraries, 2004 ACM/IEEE Joint Conference on (JCDL04), 2004.9 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)
  10. 10. Aggregation and Personalization  Collect all predicates on all sub-tracks Use road intersections to uniquely identify parts Use common sensor predicates  Query locally restricted  Aggregate all data (bias towards recent data)  Reclassify using users preference  Color map by new classification10 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)
  11. 11. Hardware  Cheap sensors: Measure vibration Low power Affordable for early adopters  Loose coupling with location system: Standard handheld GPS Use existing technology Only use timestamps to synchronize11 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)
  12. 12. Future Work  From Concept to Implementation :)  Studies for different outdoor sports Cycling Inline skating Hiking  Use this kind of WSNs in other apps highly mobile and sparsely synchronized low power and high coverage12 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)
  13. 13. Conclusion  Concept for enhancing maps with sensor information rather than just displaying values  Use Communities and enable personalization  Design aspects for mass adaptation also critical to other sensor web apps  Widen the understanding of wireless sensor networks sensors dont have to be connected all the time13 A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)

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