Info.nl organized a knowledge session on Big Data on August 9. In this presentation Sebastiaan Raaphorst of Locatienet shows how (mobility) data can generate insights and can be basis for new services.
2. Actief op gebied van routeplanning en geografische diensten sinds 2001
Sind 2004 onderdeel van de PTV GROUP
´ Verkeersoptimalisatie
´ Transportplanning
´ Rit en routeplanning
Op de consumentenmarkt vooral bekend van www.routenet.nl
www.ptvbenelux.com
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3. BIG DATA @LOCATIENET
Data gegenereerd door bezoekers Routenet
- tijdstip
- bestemming, vertrek lengte etc
- waar gaan routes lang
Verkeersinformatie
- files, aantal , lengte, oorzaak, trend
- files op een route van gebruiker
Verkeersmetingen
- aantal voertuigen (loop detectors)
- snelheid voertuigen (loop detector)
- reistijd tussen A + B (camera)
Smart phone tracking
- meten van mobiliteitspatronen van gebruikers
www.ptvbenelux.com I pag. 3
17. Sunset project
• EU's Seventh Framework Programme (FP7)
• Stimulering van innovatie
• Consortium, universiteiten onderzoeksinstellingen
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18. Sustainable mobility
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19. Sustainable mobility
• We aim for reduced congestion, reduced air
pollution or improved safety by stimulating people
to change their travelling behaviour.
• We investigate how positive incentives can stimulate
smart and sustainable traveling in urban regions.
• 1. Smart phone application senses behavior
• 2. System issues incentives , e.g. travel by bicycle and
get a free coffee
• 3. Smart phone application monitors impact of
incentives.
• 3 Living labs Enschede, Gotenborg and Leeds
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20. How
• Locatienet’s focus in the
project is the collection
analysis of measurement
data.
• Application measures and
provides feedback
• Application is ubiquitous,
runs silently in the
background no need to
start / stop
• Measurements are
analyzed on a server
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21. Sensing
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22. Sensing
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23. Measurement strategy
Smartphone has
many sensors. Some
of them use more
energy than others.
Use them smartly.
GPS & Networking
consume most
energy.
Radio, Accelerometer
and compass are
more efficient
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24. Accuracy v.s. Batery usage
User leaves home
100% charge
Normal line = static
Dotted line = travel
Back home 60 %
Phone in charger
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25. Basic data = simple
• Timestamp of measurement
• Position (lat / lon)
• Speed (GPS if available)
• Heading (GPS / Compass)
• Quality indicator (measurement error in meters)
• Measurement type
• Battery level
• Data gets a meaning if combined with other data:
− Maps (road network)
− Point of interest
− Other users
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27. Measurement quality
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28. One way streets & Ferry
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29. Sports
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30. Modality Detection
• Decision tree based on measurement characteristics
− speed, max speed, acceleration, number of turnss, distance
Detected
modality
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31. Modality # trips
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32. Modality Time
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33. Modality Distance
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34. Places
Circles indicate
places where trips
start or stop.
Red = often
Blue = less frequent
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35. Places Home Detection
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36. Places home time distribution
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37. Place ? distribution
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38. Place Work
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39. Trip purpose
Knowledge about places gives
information about the purpose of a
trip:
Work à Home = Going home
Home à Supermarket = Shopping
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40. Route Alternatives Home Work
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41. Route alternatives work home
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42. Questions
Contact details:
• sebastiaan@locatienet.com
• +31 6 51312562
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