There is more to Context than Location Albrecht Schmidt, Michael Beigl, and Hans-W. Gellersen Telecooperation Office (TecO), University of Karlsruhe, Elsevier,

There is more to Context than Location

Albrecht Schmidt, Michael Beigl, and Hans-W. Gellersen

Telecooperation Office (TecO), University of Karlsruhe,

Elsevier, 1999

2008-09-24

Presentation by JongHeum Yeon, IDS Lab.

Copyright 2008 by CEBT

Contents

Introduction

Related Work

A Working Model for Context-Aware Mobile Computing

Enhancing Ultra-Mobile Devices with Sensors

Sensor Fusion for Context Awareness

Discussion

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Introduction

Ultra-mobile devices

computing devices which can be used while on the move

Personal Digital Assistants (PDAs)

Mobile phones

Wearable computers

Context-awareness in mobile computing

Awareness of the physical environment surrounding a user and their ul-tra-mobile devices

Aim of this paper

Introduction of working model for context

Sensor-based context-awareness

Present a prototype that demonstrates the utility of sensor integration in ultra-mobile devices

Integration of multiple sensors and sensor fusion to obtain context in-formation

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Related Work

Active Badge

Use only location as context

GPS, GSM(cell information)

Stick-e-notes

Documents tagged with location and time information

Cyberguide & GUIDE

Location

User preference with an awareness

Smith et al

Integrating a few environmental sensors

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A Working Model for Context

In 1999, lack of generality of the concept and models

Propose a simple working model for context

primarily as means to position their work on sensor-based context-awareness.

Model

A context describes a situation and the environment a device or user is in.

A context is identified by a unique name

For each context a set of features is relevant

For each relevant feature a range of values is deter-mined (implicit or explicit) by the context.

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A Working Model for Context (cont’d)

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A Working Model for Context (cont’d)

Human Factors

Information on the user

– knowledge of habits/emotional state/biophysiological conditions/...

User’s social environment

– co-location of others/social interaction/group dynamics/…

User’s tasks

– spontaneous activity/engaged tasks/general goals/...

physical environment

Location

– absolute position/relative position/co-location/...

Infrastructure

– surrounding resources for computation/communication/task performance/...

Physical conditions

– noise/light/pressure/...

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Acquiring Context

Explicitly

By requiring the user to specify

e.g. Current Location

Implicitly

By monitoring user and computer-based activity

e.g. monitoring of user interaction to turn of a device after a period of inactivity

e.g. monitoring of battery power for adaptation of power-in-tensive applications

Acquisition of context

Smart environments

Embed sensors in ultra-mobile devices

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Sensor Technology

Optical/Vision

photo-diode, color sensor, IR and UV-sensor, etc.

wavelength, sunlight, type of artificial light, main color, mo-tion, detection of objects, landmarks, people, gestures, etc.

Audio

microphone, etc.

loudness, type of background noise, base frequency, speaker identification, etc.

Motion

mercury switches, angular sensors, accelerometers

moving the device, located on a table, driving in a car, etc.

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Sensor Technology (cont’d)

Location

location sensor, GPS, cellular network, radio beacon, etc.

position, location, co-location, proximity of users, devices, environment

Bio-Sensors

pulse, skin resistance, and blood pressure, etc.

emotional state, etc.

Specialized sensors

touch, temperature, air pressure, gas concentration, radia-tion, etc.

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Sensor-based Context-Awarenessfor Adaptive PDA User Interfaces

Light-Sensitive Display

Light sensor in a Palm Pilot

Awareness of surrounding lighting conditions

Control of its display’s backlight

Orientation-Sensitive User Interface

PDA, a Newton MessagePad

Awareness for its orientation by adding two mercury switches

Switch display mode between portrait mode and landscape mode

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Sensor-based Context-Awarenessfor Adaptive PDA User Interfaces (cont’d)

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Architecture for Sensor Fusion

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Cues

Scripting

Contexts

Sensors

Whilea context

Leavinga context

Enteringa context

LogicalPhysical

Situation User



Sensors

Physical sensors

– Electronic hardware components that measure physical param-eters

Logical sensors

– Information gathered from the host of the awareness compo-nent

Cues

Abstraction from physical and logical sensors

Taking the values of a single sensor up to a certain time as input and providing a symbolic or sub-symbolic output

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Contexts

Description of the current situation on an abstract level derived from the cues

Two-dimensional vectors

– symbolic value describing the situations

– a number indicating the certainty that the user (or the device) is currently in this situation

Scripting

provides mechanisms to include context information in application

Entering a context

– if a certain situation is indicated with a probability that is higher than a threshold an action is performed after a certain time#

Leaving a context

– if the probability for a certain situation is becoming less than a threshold an action is performed after a certain time.

While in a context

– if a certain situation is indicated with a probability higher than a threshold an action is performed every specified time interval.

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Deriving Context from Sensor Data

Sensor data is processed according to the architecture from sensor to cues and from cues to context

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Context Cues

In the office Artificial light, stationary or walking, room tem-perature, dry

Jogging Natural light (cloudy or sunny), walking or running, dry or raining, high pulse


Discussion

Pros

Real implementation with sensors

Mapping raw data to abstract concepts as context

Cons

Published in 1999

Not propose a general model

Context data and processing are mixed in the architecture

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