A Platform for Location Aware Service with Human Computation, PLASH

Mission-oriented Project

Presenter: Meng Chang Chen

Ling-Jyh Chen, Meng Chang Chen, Sheng-Wei Chen, Jan-Ming Ho, Wang-Chien Lee, Jane Liu, De-Nian Yang

Intelligent & Ubiquitous Computing Center

Technical DevelopmentMobile Networking & CommunicationMultimedia Content ManagementVirtual infrastructure for interactive cloud app.

PlatformsPLASH

Industrial Collaboration

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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

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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

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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.

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<VID, GPS Position, Time, other info>

<VID, GPS Position, Time, other info>

Volunteers send information periodicallyScenario 1: traffic estimation and dynamic routing

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Jammed Area

1. System derives traffic conditions.

Green Area

Green Area

Green AreaGreen Area

Jammed Area

Jammed Area

Re-routed navigation

Original navigation2. System derives a route.

4. Dynamic reroute.3. Now it is jammed!

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<Parking Available>

<Looking for Park space>

Scenario 2: available parking locating: V2V

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3G, WiMax

802.11gUsers (source)

Mobile AP(taxi, bus)

Destination

Mobile Access Cluster

Scenario 2: available parking locating: V2I2V

PLASH Architecture

Communication layer

Data layer

Service layer

V2I, V2V

Data representation, storage and access Data representation, storage and access

Fundamental servicesFundamental services

Massive data mining

Massive data mining

Literacy EnablingService

Literacy EnablingService

Geo-location query

Geo-location query

Localized data

assimilation

Localized data

assimilation

Map N’

Track

Map N’

Track

Itinerary recommen

dation

Itinerary recommen

dation

Friend compass

Friend compass

Applications

Technologies

City Profiling

City Profiling

Related Works (1) – HandoutProject PLASH Reality Mining GeoLifeWho CITI, AS MIT Media Lab MS Research Asia

PI(s) Meng Chang Chen, et al. Sandy PentlandXing Xie and Yu Zheng

Data Collection Mobile Phone w/ GPS and 3GMobile phone w/ Bluetooth

Mobile phone w/ GPS /3G

Data SourceHuman 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 ProcessingData 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.• Support location award applications with novel technologies – e.g., massive data mining, image-assisting positioning.• Provide a location-based dataset benchmark for various research.

Mining human relationships and behavior

Social Networking Service

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Related Works (2) - HandoutProject PLASH ShanghaiGrid CarTel

Who CITI, ASScience & 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 3GCommercial GPS receivers/ GPRS

Sensors on Vehicles / WiFi

Data SourceHuman Computation and Volunteering Contribution with Location Aware Applications

Collected from 6,850 taxies and 3,620 buses

Collected from sensors on 27 vehicles

Data Process Real-time / Post ProcessingReal-Time / Post Processing

Prost Processing

Data Representation

Mobile Phone/Web Traffic Contral Center 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.• Support location award applications with novel technologies – e.g., massive data mining, image-assisting positioning.• Provide a location-based dataset benchmark for various research.

Provide intelligent transportation services to improve traffic condition

Mobile Sensor Networks

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Related Works (3?) - HandoutProject 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. Gatica-Perez

Data Collection Mobile Phone w/ GPS and 3GSensors on Vehicles / WiFi

Mobile Phone

Data SourceHuman 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 ProcessingData 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.• Support location award applications with novel technologies – e.g., massive data mining, image-assisting positioning.• Provide a location-based dataset benchmark for various research.

Mobile Sensor Networks

Daily Life Patterns

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S W

O T

SWOT Analysis

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

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V2I, V2V

Data representation, storage and access Data representation, storage and access

Fundamental servicesFundamental services

APP 1APP 1 APP 2APP 2 APP nAPP n

Communication layer

Data layer

Service layer

Matured application logic becomes a fundamental service

PLASH Future Architecture

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APP 1APP 1 APP 2APP 2 APP nAPP n

Standard APIsStandard APIs

PLASH PlatformPLASH Platform

External Application

Server

External Application

Server

APIs •Authentication (login/logout)•Friend relation•Store location data•Query location data•Query Point of Interest•..•..•..•..• ..

Volunteer can use APIs to build and upload new applications

PLASH Future Architecture – Example

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Coupons On the

Go

Coupons On the

Go

Standard APIsStandard APIs

PLASH PlatformPLASH Platform

Coupon ServiceCoupon Service

Coupon DB

Let me know if my user is within 100 metersnd towards me.

Volunteer builds an e-coupon service

Geo-Range query

Geo-Range query

PLASH Future Architecture – Example

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Coupons On the

Go

Coupons On the

Go

Standard APIsStandard APIs

PLASH PlatformPLASH Platform

Coupon ServiceCoupon Service

Update location data

Coupon DB

Geo-Range query

Geo-Range query

Find a user satisfying the range query

Send the user an e-coupon

PLASH Future Architecture

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Standard APIsStandard APIs

PLASH PlatformPLASH Platform

Coupon ServiceCoupon Service

Real-Time Traffic

Real-Time Traffic

Route Suggestion

Route Suggestion

Other Location-Based ServicesOther Location-Based Services

APP 1APP 1 APP 2APP 2 APP nAPP n

Hopefully many volunteer services built on PLASH

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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