a community platform for auto-annotated recreational maps

A Community Platform for Auto-Annotated Recreational Maps

Till Riedel1, Phillip Scholl1, Christian Decker1 and Michael Beigl2

1TecO,Universität Karlsruhe(TH), Vincenz Prießnitz Str. 376131 Karlsruhe, Germany

<{riedel,scholl,cdecker}@teco.edu>

2IBR,Universität Braunschweig, Mühlenpfordstr. 23Braunschweig , Germany

<[email protected]>

mailto:cdecker%[email protected]

mailto:cdecker%[email protected]

A Community Platform for Auto-Annotated Recreational Maps (SWDMNSS 2007)2

Motivation Recreational maps Outdating Specialized

City map Karlsruhe:

still using Version from 1990 (or Google maps :-) )

Skate map Karlsruhe:

Specialized AnnotationShould have newest version !


Recreational Maps

Specialized for sport, degree of expertise more detailed annotation = better map road size doesn't matter Road quality reflected in coloring/style

Not many print runs depending on sport Out-dating rapidly:

Nature Minor road work


Alternative:Track sharing communities

Large Community Sharing single tracks Simple or text based

annotation Subjective/Biased


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 annotation


Minimal effort Automate process as much as possible

Minimal cost Use available technology

Minimal risk Anonymization: don't share raw personal data

Community Platform for Auto-Annotated Recreational Maps


(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 communication


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 user

Track Classification


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 (JCDL'04), 2004.


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 classification


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 synchronize


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 coverage


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 don't have to be connected all the time

a community platform for auto-annotated recreational maps

Technology