the ontology model and reasoner to build an autonomic system for u

DPNM, POSTECH Master Thesis Defense 1/24

The Ontology Model and Reasoner to

Build an Autonomic System

for U-Health Smart Home

Jin Kim

DPNM Lab.

Department of Computer and Communications EngineeringPOSTECH, Korea

[email protected]

December 21, 2009


Agenda

I. Contents and Motivation

II. Objective

III. State of Arts

IV. Proposed Solution

V. Implementation and Tests

VI. Conclusion & Perspectives


Contents and Motivation

Aging society and Health cost problemReduce the healthcare costs of elderly

Abuse and neglect of senior citizens

Bring healthcare to remote locations

Among elderly, falls(60% at home) is leading cause of injury and hospital admission

Why is it complex?Understand the health support for elderly at home

Understand the behavior of elderly at home

Heterogeneity of technologies at home

Medical symptoms are complex

=> Requires the convergence of technologies and knowledge

U-health Smart Home is one of the

possible solutions


Objective

General question: How web semantic

technologies can help to build a U-Health smart

Home?

Question 1: Is it possible to create model to capture

all the details of the smart home and the elderly

situation (including health) at home?

Question 2: Is it possible to build some kind of

autonomic decision making system that can use this

semantic model to manage any elderly situation at

home without any human intervention?


State of Arts(1/3) – Smart Home Projects

Project Organization Year Target Characteristic

Center for Future Health Rochester Univ. 1998 ~ Medical care Proactive health system that supports the

personal health care needs of all

Aware Home Research

Initiative

Georgia Institute of

Technology

2000 ~ User`s convenience Aimed at addressing the fundamental technical,

design, and social challenges for people in a

home setting

MavHome project Texas Univ. 2002 ~ User`s convenience Sense and predict the occupants’ mobility habits

and their use of electrical appliances

Medical automation

Research Center

Virginia Univ. 2003 ~ Medical care Molecular automation, technologies to promote

dignified aging, medical efficiency technology, etc.

Smart home program Duke Univ. 2003 ~ User`s convenience Student actually reside in home

CodeBlue project Harvard Univ. 2004 ~ Medical care infra Develop the wireless infrastructure for emergency

medical care

CASAS Washington State Univ. 2005 ~ User`s convenience Intelligent home environment, multi-disciplinary

research project

IRIS Institute for Rebabilitation

Republic of Slovenia

2007 ~ Medical care Persons with disabilities and elderly persons

Nokia Smart Home Nokia Research Center 2007 ~ User`s convenience Building an open ecosystem for digital home

control

House_n Massachusetts Institute of

Technology

- User`s convenience Focus on how the design of the home and its

related technologies, products, and services

should evolve to better meet the opportunities and

challenges of the future


State of Arts(2/3) – Autonomic Computing

What is Autonomic Computing?

Initiated by IBM in 2001

• To develop computer systems capable of self-management

• To overcome the rapidly growing complexity of IT

management

Define the MAPE architecture

• MAPE: Monitor, Analyze, Plan, Execute

Introduce the concept of Knowledge Base (KB)

• Database that contains all the knowledge necessary to the

autonomic computing to achieve self-management

• Based on a semantic model

(*) Other approaches are model less:

• AI approaches (Bio-inspired, etc.)


State of Arts(3/3) – Semantic Web Technologies

What is Semantic Model?It is an abstract view that captures all the concepts and relationships within a domain

What is Ontology?It is a formal representation of the semantic model

Ontology is used to formally define domains

What is Description Logic (DL)?Description logics are a family of knowledge representation language which can be used to represent the concept definitions of an application domain in a structured and formally well-understood way

What is OWL?It is an Ontology language for defining and instantiating Web Ontology

Allows to define concepts, relations, and facts (based on DL)

Standard from W3C

What is Reasoner?The Reasoner is a piece of software to infer logical consequences from a set of asserted facts or axioms

It is interdisciplinary, covering research in, e.g., philosophy, logic, AI, statistics, cognitive science, law, psychology, mathematics, and the sciences


Synthesis

Smart Home

Autonomic

System

Semantic

Web

Technologies


Proposed Architecture for Smart Home (1/3)

What are the requirements?

Health care part

Hospital / doctor

Specialized organization

Remote diagnosis

Autonomic computing part

Information filtering / aggregation

Situation / context modeling

Intelligence reasoning

Decision making

Home networking part

Information gathering

Service discovery

Appliance discovery

Sensing part

Nano / Bio sensor

Environment sensor

ActuatorHome control unit

Home automation

Smart Home



Home Sensor Network Autonomic System

Medical Sensor Network

Sensor

Aggregation

node

Internet

Hospital ( Control System )

Sensor

Sensor

Monitor

Analyze

Plan

Execute

Knowledge

Home Gateway

Appliances


Detailed Architecture for the Autonomic System


Wired and Wireless Network

in the Smart Home

Distributed Framework

Monitor Analyze Plan Execute

InteractingP

hysic

al

En

viro

nm

en

t

Health-care

ProviderReasoningKBA

uto

no

mic

Syste

m


Specification of an Ontology Model for U-Health Smart Home: General Approach

1. CIM Classes & Relations SelectionWe inspired from the DMTF Common Information Model

CIM is an open standard that defines how managed elements in an IT environment are represented as a common set of objects and relationships between them

Advantage:• CIM is a Open and Free standard model in IT

• It is well documented

• The model is rich ( a lot of classes, relations )

Limitation:• Oriented IT and not U-Health Smart Home

• No definition of context or situation

• Many concepts required in the U-Health Smart Home do not exist

• CIM is defined in UML but not in a semantic language

Understand the semantic of the classes and their relations and select those CIM classes and relations which are useful to build our model


The result is called the SHOM

(Smart Home Ontology Model)

2. Select a Smart Home Specification Language :OWL (Web Ontology Language):

• OWL-Lite, OWL-DL, OWL-Full

3. Convert CIM classes/relations into OWL ontology model

4. Enhance the resulting model with new concepts and relations to be able to perform autonomic decisions in the U-Health Smart Home

Specification of an Ontology Model for U-Health Smart Home: General Approach


CIM Classes and Relations Selection

CIM SchemaCIM Schema = Core model + Common models

The core model captures notions that are applicable to all areas of management and represents a starting point for determining how to extend the common schema

The common models are information models that capture notions that are common to particular management areas, but independent of any particular technology or implementation

Which classes are useful for the project?CIM_Core of Core Model

CIM_Device of Common Model

CIM_System of Common Model

CIM_User of Common Model

CIM_Service of Common Model

Other not used models (may be useful in the future)• CIM_Application, CIM_Database, CIM_Event, CIM_Interop, CIM_Policy,

CIM_Network


Converting CIM to OWL

Converting the main CIM concepts into OWL

Add semantic information to the relationships between concepts

Functional

Inverse

Transitive

Symmetric

CIM OWL

Class <owl:class>

Generalization <rdfs:subClassOf>

Property <owl:DatatypeProperty>

REF Property <owl:ObjectProperty>

Min <owl:minCardinality>

Max <owl:maxCardinality>

Required <owl:minCardinality rdf:datatype=“&xsd;int”>1

</owl:minCardinality>


Enhancing the Resulting Model

CIM classes are not sufficient to model the U-Health Smart Home world

Added several concepts and relation between concepts TBox (TerminologicalBox) such as

Patient (Monitored and Not Monitored)

Sensors (Bio, Environment)

Situation (Activity, etc.)

Smart Home, Room, etc.

Used several ABox (AssertionBox) to create relations between individuals and concepts

SHOM: Proposed Smart Home Ontology Model


SHOM: Smart Home Ontology Model


Reasoning on the SHOM

What is reasoning?

Reasoning is the cognitive process of looking for

reasons, beliefs, conclusions, and actions

Reasoning is a kind of test for context recognition

and right decision making

How do we reason on an ontology?

To define reasoning rules in the ontology

To use a reasoner that is able to reason on the

ontology (applying inner logic rules + the defined

rules)



How to define rules?

SWRL (Semantic Web Rule Language) is a

proposal for a Semantic Web rules-

language, combining sublanguages of the

OWL Web Ontology Language (OWL DL

and Lite) with those of the Rule Markup

Language

SWRL uses logic operators to define rules

• AND, OR, NOT, {¬, ∃, ∍, ∩, ∪}

SWRL rules are stored in the ontology as

concepts



Example of rule to identify elderly situation and take an autonomic decision:

If the elderly is in his bed and the TV is off and the Light is Off, then the elderly is sleeping

If the elderly is sleeping, then set the temperature in the room to 27 degrees

SWRL Formal Specification:

isInRoom(?x, bedroom) ∧hasApplianceState(tv_bedroom, false) ∧hasApplianceState(light_bedroom, false) → hasUserActivityState(?x, SleepingActivityState)


Implementation and Tests

Development environments

Protégé 3.4.1 and 4.0

JAVA SE Runtime environment 1.6.0

Eclipse SDK 3.5.1

Pellet API 2.0.0 & OWL API 2.2.0

Defined classes in the SHOM

Whole classes (103)

Defined TBox and Concepts Properties

Object property (26) + Data property (37)


Conclusion(1/2)

Question 1: Is it possible to create model to capture all

the details of the smart home and the elderly situation

and health?

We have proposed an ontology model (SHOM) to capture the

concepts of the U-Health Smart Home. We have used

successfully the ontology concepts to capture the semantic of

the relations between several entities in the home

Question 2: Is it possible to build some kind of autonomic

decision making system that could take care of the

elderly at home without any external help for many

situations

We have used SHOM to define semantic rules to capture the

situation of the elderly at home. And based on this situation we

have shown how we can enforce some autonomic decisions


Conclusion(2/2)

ContributionInitial specifications of a semantic model for U-Health Smart Home and initial autonomic decision-making

LimitationThe model and autonomic decision are only a first initiative that should be developed extensively taking into account real situations

Future workEnhance the model and reasoning part

Interface the autonomic system with the other components of the autonomic system

Perform some real tests in the POSTECH Smart Home to understand elderly behavior at home


Thank you

Q&A


Appendix


Reasoner Comparison

Bossam Pellet KAON2 RacerPro Jena FaCT++

OWL-DL

entailment

yes yes yes Yes

Supported

expressivity

for

reasoning

SROIQ(D) SHIQ(D) SHIQ(D-) SROIQ(D)

Reasoning

algorithm

Rule-based Tableau Resolution

& Datalog

Tableau Rule-based Tableau

Consistency

checking

yes yes Incomplet

for OWL DL

Yes

DIG support no yes yes yes yes Yes

Rule

support

SWRL &

own rule

format

SWRL SWRL SWRL-Not

fully support

& own rule

format

Own rule

format

No

Licencing Free/closed-

source

Free/open-

source &

nonFree/clo

sed-source

Free/closed-

source

Nonfree/clo

sed-source

Free/open-

source

Free/open-

source


CIM MOF File Style

MOF File Contents (ex: PhysicalElement )

// Copyright (c) 2005 DMTF. All rights reserved.

// <change cr="SysDevCR00714.001" type ="change">Update of

// descriptions based on Tech Edit review.</

// <change cr="ArchCR00066.004" type="add">Add UmlPackagePath

// qualifier values to CIM Schema.</change>

// ==================================================================

// CIM_PhysicalElement

// ==================================================================

[Abstract, Version ( "2.10.0" ),

UMLPackagePath ( "CIM::Core::Physical" ),

Description (

"Subclasses of CIM_PhysicalElement define any component of a "

"System that has a distinct physical identity. Instances of "

"this class can be defined as an object that can be seen or "

"touched. All Processes, Files, and LogicalDevices are "

"considered not to be Physical Elements. For example, it is not "

"possible to touch the functionality of a \'modem.\' You can "

"touch only the card or package that implements the modem. The "

"same card could also implement a LAN adapter. PhysicalElements "

"are tangible ManagedSystemElements that have a physical "

"manifestation of some sort. \n"

……..

class CIM_PhysicalElement : CIM_ManagedSystemElement {

[Key, Description (

"An arbitrary string that uniquely identifies the "

"Physical Element and serves as the key of the Element. "

"The Tag property can contain information such as asset "

"tag or serial number data. The key for PhysicalElement “

………

MaxLen ( 256 )]

string Tag;

……….


CIM UML example(1/2)


CIM UML example(2/2)

SettingDefineState

- Initial value setting

ElementSettingData

- current value setting

SettingsDefineCapabilities

- limitation of value


Whole Classes Taxonomy


Whole Classes with Object Properties


ManagedElement Class


PhysicalElement Class


LogicalDevice and State Class


UserEntity and UserActivityState Class


ManagedSystemElement and Organizaiont Class


Snapshot Using Protégé Tool

Protégé 4

For OWL 2

Protégé 3.4.1

For SWRL


Autonomic System by IBM

Four common managed resource arrangements

Autonomic computing reference architecture

the ontology model and reasoner to build an autonomic system for u

Documents