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Location Modeling and Machine Location Modeling and Machine Learning in Smart EnvironmentsLearning in Smart Environments

Robert WhitakerRobert Whitaker

Supervisor: A/Prof Judy KaySupervisor: A/Prof Judy Kay A/Prof Bob KummerfeldA/Prof Bob Kummerfeld

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OverviewOverview

Problem Previous Work Possible Data Sources Tools Available Issues

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Thesis TopicThesis Topic

Explore ways of determining a persons current location and activity

Explore ways of predicting a persons location/activity using Location Modeling and Machine Learning

The results returned must be scrutable

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Possible SituationPossible Situation

Where’s Boris Scenario Wish to organize a meeting with

another person where the time suits both parties

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Possible StepsPossible Steps

Contact the person you wish to meet Both people would look at their

schedules and negotiate a time Both parties agree on the time they are

to meet

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Possible ProblemsPossible Problems

One of the persons schedule may be incomplete

When you arrive at the meeting time the person is not there. Should you wait? Where is the person?

What if you can’t connect the person to organise the meeting

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High Level ViewHigh Level View

PDA

Machine Use Saving of RawData Database of Raw

Facts

Conversion intoLogical

RepresentationDatabase ofLogical DataUser Model

Creator - personisData store of

model info

User

Where is X mostlikely to be?

Build Result Setusing Markov

Model

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Previous WorkPrevious Work

Active Badge Project Lancaster Guide Project Doppelganger Activity Compass Project

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Active Badge ProjectActive Badge Project

First Indoor positioning system Users wear badges to emit their

location Applied to teleporting Active Bat project extended the basic

concepts developed

Source: Nigel Davies and Hans-Werner Gellersen Beyond Prototypes: Challenges in Deploying Ubiquitous Systems. IEEE Pervasive Computing, Volume 1 (Jan-March 2002). 26-35.

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Lancaster Guide ProjectLancaster Guide Project

A tourist guide for the city of Lancaster Used tablet PC’s connected to a

802.11 network Limited by the infrastructure

capabilities.

Source: 1. Nigel Davies and Hans-Werner Gellersen Beyond Prototypes: Challenges in Deploying Ubiquitous Systems. IEEE Pervasive Computing, Volume 1 (Jan-March 2002). 26-35.2. The Guide Project, http://www.guide.lancs.ac.uk

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Lancaster Guide InterfaceLancaster Guide Interface

Source: The Guide Project, http://www.guide.lancs.ac.uk

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DoppelgangerDoppelganger

Generalized tool for gathering, processing and providing information about users

Learning Techniques Beta Distribution Linear Prediction Markov Models

DopMail

Source: Orwant, J., Heterogeneous Learning in the Doppelganger User Modeling System. in User Modeling and User-Adapted Interaction, (1995), 107-130.

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DoppelgangerDoppelganger

Applications

BetaDistribution

Linear Prediction

MarkovModels

LearningToolboxSensors

Source: Orwant, J., Heterogeneous Learning in the Doppelganger User Modeling System. in User Modeling and User-Adapted Interaction, (1995), 107-130.

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Activity Compass ProjectActivity Compass Project

Location Modeling to help disabled PDA device application developed to

assist with location tracking Tracking movements and comparing

them to a map Prediction algorithms used Relational

Markov Models

Source: Patterson, D.J., Etzioni, O. and Kautz, H. The Activity Compass, University of Washington, 2003.

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Prototype of Activity CompassPrototype of Activity Compass

Source: Patterson, D.J., Etzioni, O. and Kautz, H. The Activity Compass, University of Washington, 2003.

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Possible Data SourcesPossible Data Sources

Bluetooth Devices Machine Learning

Windows Based Unix Based

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ToolsTools

Personis Elvin Messaging Bspy Markov Modeling Toolkits Manual Logs for Evaluation Purposes

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PersonisPersonis

User modeling software Accretion representation

Consists of components which model aspects of the user

Allows the user model to be scruntised

Source: Kay, J., Kummerfeld, B. and Lauder, P., Managing private user models and shared personas. in Workshop on User Modelling for Ubiquitous Computing, (Pittsburgh, USA, 2003).

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Example of User ModelExample of User Model

Output from Personis: Modeling the locations where the user has been

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Elvin MessagingElvin Messaging

Publish/Subscribe Messaging System Messages routed by content Application: sending messages

between sensors and modeling software

Elvin Router

Client

Client Client

Client

Source: Mantara Software Elvin Administrator's Guide, 2003.

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BspyBspy

Bluetooth positioning system Detects Bluetooth devices and logs

them to a database Uses Elvin messages to send

information from sensor to database

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Example DataExample Data

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Markov Modeling ToolkitsMarkov Modeling Toolkits

Hidden Markov Modeling Package – Python

Matlab Hidden Markov Package Markov Chain Algorithm Cambridge Markov Modeling Toolkit

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Manual LogsManual Logs

Records activity and location in 15 min blocks

Provides some example data to develop the algorithms off

Used for the evaluation of the learning algorithm

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Code SheetCode Sheet

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Manual LogManual Log

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Research IssuesResearch Issues

Representation of location and activity Creation of data sets Modeling Time

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QuestionsQuestions