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, WangChien Lee, Jane Liu, De-Nian Yang
Presenter: Meng Chang Chen
Intelligent & Ubiquitous Computing Center
Technical Development
Mobile Networking & Communication
Multimedia Content Management
Virtual infrastructure for interactive cloud app.
Platforms
PLASH
Industrial Collaboration
+
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
3
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
4
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.
5
<VID, GPS Position, Time, other info>
Volunteers
information
periodicallyand
Scenariosend
1: traffic
estimation
<VID, GPS Position, Time, other info>
dynamic routing
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1. System derives traffic conditions.
Jammed Area
Jammed Area
Green Area
Green Area
Green Area
Green Area
4. Dynamic reroute.
3. Now it is jammed!
Jammed Area
2. System derives a route.
Original navigation
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Re-routed navigation
Scenario 2: available parking locating: V2V
<Parking Available>
<Looking for Park space>
8
Scenario 2: available parking locating: V2I2V
3G, WiMax
Mobile AP
(taxi, bus)
Destination
802.11g
Users (source)
Mobile Access Cluster
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PLASH Architecture
Applications
Map N’
Track
Itinerary
recommen
dation
Friend
compass
Massive
data mining
Service layer
Technologies
Fundamental services
Literacy
Enabling
Service
Data representation, storage and access
Geo-location
query
V2I, V2V
Localized
data
assimilation
Data layer
City
Profiling
Communication layer
Related Works (1) – Handout
Project
PLASH
Reality Mining
GeoLife
Who
CITI, AS
MIT Media Lab
MS Research Asia
PI(s)
Meng Chang Chen, et al.
Sandy Pentland
Xing Xie and Yu Zheng
Data Collection
Mobile Phone w/ GPS and 3G
Mobile phone w/ Bluetooth Mobile phone w/ GPS /3G
Data Source
Human Computation and Volunteering Contribution with
Location Aware Applications
Monitor 100 mobile
phones over 9 months
Upload by users
Data Process
Real-time / Post Processing
Post Processing
Real-time Processing
Data Representation
Mobile Phone/Web
None
Mobile Phone/Web
Objective
• Build a platform for Location Aware Service with layered
architecture.
• Provide a standard AIP for other application builder.
• Create City Profiling for traffic estimation, network
performance monitoring, city trend analysis, etc.
Mining human
• Support location award applications with novel
relationships and behavior
technologies – e.g., massive data mining, image-assisting
positioning.
• Provide a location-based dataset benchmark for various
research.
Social Networking Service
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Related Works (2) - Handout
Project
PLASH
ShanghaiGrid
CarTel
Who
CITI, AS
Science & Technology
Department of Shanghai
MIT CSAIL
PI(s)
Meng Chang Chen, et al.
Minglu Li and Lionel M. Ni H. Balakrishnan, et al.
Data Collection
Mobile Phone w/ GPS and 3G
Commercial GPS receivers/
Sensors on Vehicles / WiFi
GPRS
Data Source
Human Computation and Volunteering Contribution with
Location Aware Applications
Collected from 6,850 taxies Collected from sensors on
and 3,620 buses
27 vehicles
Data Process
Real-time / Post Processing
Real-Time / Post Processing Prost Processing
Data Representation
Mobile Phone/Web
Traffic Contral Center
Objective
• Build a platform for Location Aware Service with layered
architecture.
• Provide a standard AIP for other application builder.
Provide intelligent
• Create City Profiling for traffic estimation, network
performance monitoring, city trend analysis, etc.
transportation services to
improve traffic condition
• Support location award applications with novel
technologies – e.g., massive data mining, image-assisting
positioning.
• Provide a location-based dataset benchmark for various
research.
None
Mobile Sensor Networks
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Related Works (3?) - Handout
Project
PLASH
CarTel
Multmodal Daily Life
Patterns
Who
CITI, AS
MIT CSAIL
EPFL, Switzerland
PI(s)
Meng Chang Chen, et al.
H. Balakrishnan, et al.
K. Farrahi and D. GaticaPerez
Data Collection
Mobile Phone w/ GPS and 3G
Sensors on Vehicles / WiFi Mobile Phone
Data Source
Human Computation and Volunteering Contribution with
Location Aware Applications
Collected from sensors on
27 vehicles
Monitor 97 users over
10 months
Data Process
Real-time / Post Processing
Prost Processing
Post Processing
Data Representation
Mobile Phone/Web
None
None
Objective
• Build a platform for Location Aware Service with layered
architecture.
• Provide a standard AIP for other application builder.
• Create City Profiling for traffic estimation, network
performance monitoring, city trend analysis, etc.
Mobile Sensor Networks
• Support location award applications with novel
technologies – e.g., massive data mining, image-assisting
positioning.
• Provide a location-based dataset benchmark for various
research.
Daily Life Patterns
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SWOT Analysis
Helpful
Harmful
to achieving the objective
to achieving the objective
(Attributes of the Environment) (Attributes of the
Organization)
External Origin
Internal Origin
Strong team of various background Lack of experienced programmers
S
O
W
T
Innovative system design using
“human computation”
Difficult to recruit users
Location aware applications bring
opportunities and challenges for
technologies development and
research.
Strong competitors
Throat chokehold by Google map
& carriers
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

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Future Work
•
Deploy and 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.
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PLASH Future Architecture
Matured application logic becomes a fundamental service
APP 1
Service layer
Data layer
APP 2
APP n
Fundamental services
Data representation, storage and access
Communication layer
V2I, V2V
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PLASH Future Architecture
Volunteer can use APIs to build and upload new applications
APP 1
APP 2
External
Application
Server
APP n
Standard APIs
APIs
PLASH Platform
•Authentication (login/logout)
•Friend relation
•Store location data
•Query location data
•Query Point of Interest
•..
•..
•..
•..
• ..
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PLASH Future Architecture –
Example
Volunteer builds an e-coupon service
Coupons
On the
Go
Coupon
Service
Coupon
DB
Standard APIs
Geo-Range
query
Let me know if my user is within 100 meters
nd towards me.
PLASH Platform
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PLASH Future Architecture –
Example
Send the user an e-coupon
Coupons
On the
Go
Coupon
Service
Update location data
Coupon
DB
Standard APIs
Geo-Range
query
Find a user satisfying the range query
PLASH Platform
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PLASH Future Architecture
Coupon
Service
APP 1
APP 2
APP n
Real-Time
Traffic
Standard APIs
Route
Suggestion
Hopefully many
volunteer
services built on
PLASH
PLASH Platform
Other LocationBased Services
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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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