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Geographic Information Infrastructuresfor Ubiquitous Computing

Spring 2007

Ki-Joune Li

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Cyber Space vs. Ubiquitous Space

VS.

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Ubiquitous Space vs. Internet Space

Internet Space

Real World

user user user

Gates to Dive into Internet Space

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Ubiquitous Space and Augmented Reality

Cyber Space

Real World

user

user

user

user

Ubiquitous Space

AugmentedReality

Bridge to connect

Cyber space and real world

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Example of Augmented RealityCase 1: Multi-Projector

[Bauhaus Institute]

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Example of Augmented RealityCase 2: Surgery

[INRIA]

[Univ. Rochester]

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Example of Augmented RealityCase 3: Pedestrian

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Example of Augmented RealityCase 3: Pedestrian

Drishti: Indoor/Outdoor Blind Navigation System

- Sumi Helal, Steve Moore at Univ. Florida, USA

Orientation

Coordinates

Geographic Context

and

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Types of Augmented Reality ?

User Types

Mobility

Personalization

General Users

Our Concern

CASE 1

Stationary ObjectsGeneral Users

CASE 2

Stationary ObjectsIndividual Users

CASE 3

Mobile ObjectsIndividual Users

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Scenario

Detection by Sensor

RetrieveContextInformation

Provide AugmentedReality

Geographic Context

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Context-Awareness

Context

Internal Context

Static Context(Information-Driven)

Dynamic Context(Sensor-Driven)

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Context-Awareness without Information Provider

Context

Internal Context

Static Context(Information-Driven)

Dynamic Context(Sensor-Driven)

We need a map !

What can we do with this compass ?

Map: Static Information

Relatively Large to fit in a small device

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Indoor Space

Road Network Space

Euclidean Space

Spatial Context-Awareness(Geographic Awareness)

SpatialContext

My Status + Location, Speed, Orientation

Geographic Information

Static Context

Geo-Sensor

Dynamic Context

Internal Context

Seamless Space

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Geo-Labeling: Identification of Geographic Object

Context

My Status + Location, Speed, Orientation

Geographic Information

Static Context

Geo-Sensor

Dynamic Context

Internal Context

How to Identify and Retrieve Geographic Informationin Mobile Environment ?

Object Identifier orForeign Key like DB ?

We need a Mechanism to Identify a Geographic Object (Feature) and Retrieve its information

Geo-Labeling

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Geo-Label

Real World

UserRFID

2-DBarcode

Feature

Geo-Labels

GeographicDatabases

2. Complex Geographic Context Information

1. Simple Geographic Context Information

UFID

iPointer

Geo-Label

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Context-Aware Mapping

Context

My Status + Location, Speed, Orientation

Geographic Information

Static Context

Geo-Sensor

Dynamic Context

Internal Context

How to cook GI, stream data from sensors, and internal states ?

Requirements - Geographic Awareness, - Real-Time, - Scalability, and - Mobility

Approaches - Wireless Communication, - In-Network Approach like USN, P2P, or DMB

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Two Viewpoints

GeographicContext

RealWorld

1. How to get Geographic Context ?

2. How to handle Geographic Context ?

ApplicationSystems

2-1. How to provide Geographic Context ?

2-2. How to search Geographic Context ?2-3. How to analyze Geographic Context ?

1-1. How to collect Sensor Data ?

1-2. How to identify Geographic Features ?

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Challenges

To get geographic context To handle geographic context

Identification of geographic features

Geographic context in Heterogeneous Spaces

Providing geographic context

Analysis of geographic context

Scalability problem

Geo-Label

Indoor Underground 3-D

In-NetworkProcessing

DistributedMiddleware

Egocentric Mapping

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How to Implement Geo-Labels

Geo-Label: A label for recognizing geographic feature

Implementation Physical Device

2-D Bar Code RFID

Virtual Geo-Label Dynamic Computation from Viewpoint

Contents of Geo-Labels UFID u-Location Other Information

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2-D Bar Codes

Home Page URL,UFID,u-Location, andOther Information

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Virtual Geo-Labels

No Physical Devices Dynamic

Computation of Geo-Labels Position View Direction Velocity

Real World

Augmented Realityon a screen

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Implementation of Virtual Geo-Label in 3-D

Server of 3-DGIS Databases

Server ofApplication DB

Geo-Label Mobile Client

Position

Velocity

Interest

View Point

Geo-Label

DynamicComputation

Presentation of UsefulInformation

Progressive Transfer

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Heterogeneous Space

Euclidean Space No obstacle to movement or placement

Constraint Space Many obstacles in reality Indoor space, Road Network space, and Terrain space Representation of Constraints

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Example: Indoor Space

No more Euclidian Space Different coordinate systems and different properties.

We should rebuild Spatial DBMS for Indoor Space

Emergency Bell A

401

W.C.

404

405

406

ElevatorStairs

Emergency Bell Bp (F4, 401, 15, 18)

4th Floor

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Should be processedin Real-Time

Large Number of Nodese.g. 1 Million Nodes

→ 1 sec/ node

Scalability and Real-Time Constraint

Geographic Context

MobileNode

MobileNode

DynamicUpdates of

Position

ContextRequest

MobileNode

MobileNode

MobileNode

MobileNode

MobileNode

MobileNode

GIS DBGIS DBLocation DBstationary and mobile nodes

Location DBstationary and mobile nodes

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Server

Geographic Context-Awareness by In-Network Processing

Scalability Problem

Each node has a small fraction of geographic Information.

Each node exchanges geographic information by

P2P Sensor Network Broadcasting

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In-Network Processing: P2P

Peer-to-Peer

No Centralized ServerOriginally for File Sharing Services

Each node has an IPv6 address Databases are scattered into mobile nodes

(x1,y1,t1), IPAddr1(x2,y2,t2), IPAddr2(x3,y4,t4), IPAddr3(x4,y4,t4), IPAddr4

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Example of P2P

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In-Network Processing: Sensor Network

Sensor Network DatabaseSensor Network Database

No Centralized ServerMobile Ad-Hoc Network

MANET Databases are scattered into mobile node

Coverage Area

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Data on Air

Data on AirData on Air

Broadcasting ServerBroadcasting like DMB

Databases are periodically broadcasted

BroadcastingGeographic Context

Broadcasting Server

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Ubiquitous Computing Architecture

Heterogeneity and Distributed Middleware

MobileNode

MobileNode

MobileNode

Middleware Middleware Middleware

MobileNode

MobileNode

MobileNode

Middleware Middleware Middleware3-Tiers Architecture

Server Server Server

Middleware

Client Client Client

Massively Distributed Environment

Binding Client and Server

Binding Mobile Nodes

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PerformanceBottleneck

Heterogeneity and Distributed Middleware

Middleware

Binding ObjectsGeographic Binding

Location Data Server

(GIS)

Mobile Node Mobile Node

Middleware Middleware

Mobile Node Mobile Node

LDS LDSStandard

e.g. SensorML

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Egocentric Mapping: Evolution of the Map

Paper Maps

Digital Maps

Mobile Maps

Intelligent Maps

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Paper Maps

Only for Visualization Static Map

Information should be preprocessed with respect to the purpose

Example Signage, Immovable Maps

Problems No consideration for a specific user

No Sign on the Location or Orientation of User on the Map Limited Attributes No Mapping Operations

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Digital Maps

A progress from paper maps Several types of operations and analysis becomes possible

Visualization such as zooming, panning and rotating Spatial analysis

No consideration about mobile users No Information about

“Where I am” User’s status

Limited mapping operations are possible Zooming, Panning Layer Selection

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Mobile Maps

Digital Map with some considerations about “Where I am” and Hardware constraints such as

Size of screen Memory size

No consideration about user’s state

Mapping operation concerning mobility such as Orientation

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Intelligent Mobile Map

Mobile Map

Consideration of user’s state

Dynamic Mapping

Mobility Information- Location- Direction- Speed

User State and Demand

Egocentric Mapping

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Egocentric Mapping

Traditional Map

userA

userB

userI

userD

userC

userF

userG

userH

Egocentric Map

user AEgocentric Map

user B

Egocentric Map

user C

Egocentric Map

user D

What you see is What you want What you want is What you see

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Example of Egocentric Mapping

Multiple LOD

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Example of Egocentric Mapping

Varying LOD

Space Contradiction

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Example of Egocentric Mapping

Information in Real-Time

Augmented Focus

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Summary

Ubiquitous Computing Location Awareness Geographic Awareness

Several Challenges to Realize Geographic Awareness Geo-Label Seamless Space

Integration of Indoor and Outdoor Spaces Heterogeneity and Scalability Issues Egocentric Mapping

Context-Aware Mapping

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But NOT LIKE THIS