Transcript Presentation Title Here

Mining Vehicular Context: The Full Spectrum
Moustafa Youssef
Wireless Research Center of Excellence @ E-JUST
Vehicular Context
• What the vehicle is doing
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Location
Speed, acceleration
Braking
Fuel consumption
• Sensors
– Cell phones
– OBD
• Ultimate goal
– Driverless cars
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
Wider Spectrum
Context
• User
– Texting
– Sleepy(ing)
– Driver, passenger
• Vehicle
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Car location
Speed, acceleration
Braking
Fuel consumption
Temperature, humidity, rain
• Environment
– Awareness of surroundings (driverless cars)
– Crowd-sensing: Traffic congestion, pollution, sound levels
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
Wider Spectrum
Sensors
• OBD
• Driver/passenger cell phone
• Special sensors
– CO2
• Unconventional sensors
– Other users/cars
– Sensor-less sensing - Device-free sensing [Youssef et al’07]
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
Challenges
• Ubiquitous/zero cost
– Cell phones/environment as a sensor?
• Heterogeneity of sensors
– Different devices, different signals
• Scale
– Millions (billions) of users
– Data size
– Data rate/bandwidth
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
Challenges
• Noise in data
– Cheap sensors
• Efficient computation/processing
– Batch/opportunistic upload
• Vs. realtime processing
– Offloading to cloud
– Local clouds (cloudlets)
• Privacy/security
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
Selected Projects
Projects
• Map++
– Crowd-sourced semantic-rich map construction
• Dejavu
– Accurate Energy-efficient GPS Replacement
• ReVISE
– Ubiquitous Car Type/Speed Estimation
• ARTS
– Ubiquitous Traffic Monitoring
Map++ [SECON’14]
• Crowd-sensing for automatic map semantic
identification
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
Map++: Basic Idea
• Different semantics have unique sensor
signature
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
Dejavu [ACM SIGSPATIAL’13-Best Paper Award]
• Accurate energy-efficient outdoor localization
• GPS replacement
• Even more accurate in in-city driving
conditions
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
Dejavu: Basic Idea
• Dead-reckoning
• Unique anchors for error-resetting
– Physical
– Virtual
PAN Det
User Traces
C
S
D
A
Anchors
PAN
Match.
Updated Anchors
VAN
Match.
Updated Anchors
New location
VAN Det
Virtual Anchors
WiFi Streams
Space
Anomaly
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Mag.F. Str.
Anomalies
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
Clustering
..
Clustering
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Det.
..
Acc. Str.
Spatial
WiFi
Clusters
GSM
Clusters
Z-grav.
Clusters
Feature-
GSM Streams
.
Pre-processing and Feature Extraction
B
Orient.
Clusters
ReVISE: Car Type/Speed [VTC’12]
• Ubiquitous transparent traffic state monitoring
• Device-free localization concept
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
ReVISE: Car Type/Speed
• Current deployment: Road side
– Car speed, human/car differentiation, car type
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
ARTS [SIGSPATIAL’14]
• Accurate and reliable road traffic estimation
– Cellular-based: single cell tower
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
Conclusions
• Wide spectrum of context information
– And sensors
• Number of challenges that need to be
addressed
• Applications avalanche effect
(c) 2014, The Wireless Research Center, E-JUST. http://wrc.ejust.edu.eg
For More Information
Project web site:
http://wrc-ejust.org/projects
Papers
Media coverage
Funded by: