CONTROL MODEL OF DOMOTIC SYSTEMS

BASED ON ONTOLOGIES

Pablo A. Valiente-Rocha and Adolfo Lozano-Tello

Universidad de Extremadura, Área de Lenguajes y Sistemas Informáticos

Escuela Politécnica, Campus Universitario s/n, 10071, Cáceres, Spain

Keywords: Ontologies, SWRL, Ambient Intelligence, Domotic, IntelliDomo.

Abstract: In the present paper we introduce the model process of an expert system for the control of domotic

installations based on ontologies and SWRL rules. From the domotic system database where the attribute

values of each device are stored, a background process converts these values into instances of the ontology

representing the system. From these instances, a software application -known as DomoRules- allows

creating production rules in SWRL language that will be useful to regulate the system. IntelliDomo draws

inferences from the ontology and the SWRL rules by using behaviour parameters previously indicated by

the user, so the state of the physic devices in the domotic system can be modified in real time.

1 INTRODUCTION

The use of Ambient Intelligence (AmI) is one of the

areas which are rapidly gaining importance in the

application of intelligent systems in companies and

homes. One of the characteristics AmI systems seek

is the gift of interaction with the user so that

communication is as far as possible natural and the

configuration of preferences takes less time for the

user. AmI systems use behaving policies able to

draw deductions with the information provided by

certain devices and the represented rules. Moreover,

they make decisions regarding the management of

the installation.

The use of ontologies as representing bases,

together with the representation of rules in SWRL in

AmI systems, will provide the most precise

definition of the taxonomy of physical devices that

may exist in a system, the attributes of these devices

and the possible relations among them. Furthermore,

these representations will be more reusable by other

users and will favor the completion of the

classification of domotic components, the useful

information to be represented upon these

components and the connection rules that will allow

deducting new information regarding the values of

other components.

The amount of literature about intelligent

domotic environments, which makes use of

ontologies as representing bases, is poor. DomoML

is one of the main reference works (Sommaruga et

al, 2005)(Furfari et al, 2004); it is a markup

language focused on defining a communication

method among domotic devices.

Related to the previous project, DogOnt (Bonino

& Corno, 2008) proposes a system able to recognize

the devices that comprise the domotic environment

automatically. DogOnt uses SWRL language to

define rules that allow completing the ontology

model which represents the domotic environment.

In these projects ontologies are used as

representing bases of domotic devices and SWRL

rules are used to maintain consistency in the

information of the system components values.

However, these production rules are not used to

control general autonomous and real time

functioning of the system.

The present paper introduces IntelliDomo, an

AmI system based on ontologies for the control of

domotic systems. It uses domotic components and

its state values represented as instances of an

ontology, and takes advantage of the power of the

production SWRL rules specified by the user in

order to change the state of the system components

in real time. In section 2 of the present paper, we

will describe the architecture of IntelliDomo and, in

470

A. Valiente-Rocha P. and Lozano-Tello A. (2010).

CONTROL MODEL OF DOMOTIC SYSTEMS BASED ON ONTOLOGIES.

In Proceedings of the 2nd International Conference on Agents and Artiﬁcial Intelligence - Artiﬁcial Intelligence, pages 470-473

 SciTePress

Figure 1: Overview of IntelliDomo Arquitecture.

its subsections, we will describe each of the

components and tools of the model software.

Finally, section 3 is dedicated to conclusions and

future lines.

2 MODEL PROCESS FOR

THE CONTROL OF DOMOTIC

INSTALLATIONS

BASED ON ONTOLOGIES

IntelliDomo is an expert system able to control the

components of a domotic system automatically and

in real time. It is based on an ontology called

OntoDomo which contains the information about the

devices of the system, on production rules in SWRL

language which shape its behaviour and on a series

of interconnection software tools, rules design and

inference motor (see Figure 1).

The main characteristic of IntelliDomo is the

ability of making decisions and reacting to the

changes that arise in the elements of the domotic

system. These decisions are taken based on the state

of the system elements represented in OntoDomo

and also on a set of established rules, expressed in

the SWRL rules definition language. These rules can

be modified by the user with the use of the

DomoRules tool presented in the following

subsection. In order to draw knowledge deductions,

IntelliDomo uses Jess inference motor, this tool will

allow inferring the concepts of the ontology and

obtaining new data according to what it is stated in

SWRL rules.

In order to manage this knowledge, IntelliDomo

is built upon an ontology which concepts are related

to the domotic components. The ontology has been

modeled to be in sync with the physic devices that

form a domotic environment, so that it can store its

outstanding values and properties.

IntelliDomo has been designed to interact with

an existing domotic database (DomoBD), where the

state and values of the domotic components are

updated in real time. This database can be obtained

throughout the QDSConnect software module that

has been developed by the research team from the

Universidad de Extremadura, Quercus. This daemon

provides the physic connection with EIB/KNX

bus(http://www.knx.org). QDSConnect uses

FALCON library to translate values of the physic

devices into the relational database system and to

detect any changes that may occur in the mentioned

database in order to modify it straight in the physic

devices.

Therefore, IntelliDomo can make deductions and

update the domotic system instantly by transferring

the new values from its hardware components to the

database. DomoBD is the link between IntelliDomo

and the physic domotic system. The information of

this database is constantly translated into instances

of OntoDomo by DBConnection Module. Similarly,

when Intellidomo fires the correspondent rules,

DBConnection Module updates DomoBD database,

which will entail the respective changes of state in

the physic devices.

2.1 OntoDomo Ontology

Nowadays, ontologies are the most used way of

knowledge representation in different business or

research projects in fields such as databases,

intelligent information integration, cooperative

information systems, information retrieval,

electronic commerce, enterprise application

integration, and knowledge management (Hepp,

2008). IntelliDomo uses ontologies as a representing

base of domotic elements that constitute the system.

These elements are stored in OntoDomo.owl, which

CONTROL MODEL OF DOMOTIC SYSTEMS BASED ON ONTOLOGIES

471

is responsible for reusing the knowledge of the rest

of ontologies constituting IntelliDomo.

IntelliDomo allows the users to establish

configurations able to guide the system behaviour

and that are adapted to its needs and preferences. In

order to do so, it uses an ontology that allows storing

the configuration into profiles and to make

inferences and reasoning able to incorporate new

knowledge to the system. The ontology

Preferences.owl is used with this end. Here, each user

will be able to store his/her personal information for a

certain situation: security, temperature, comfort... A

series of variables defining the user's preferences can

be established for every situation. For instance, as

for temperature, the user will be able to specify that

‘hot’ ranges between 25 ºC and 36 ºC, consequently,

these values will be used in the corresponding

production rules.

Besides, the ontology Preferences.owl controls

the so-called ‘system variables’. These are control

variables which could be used in SWRL rules to

work with them and draw inferences. These

variables work as global variables that will be shared

by each user and known by the inference system in

order to use them as a reference for certain

decisions. These variables are identified with the

symbol ‘#’ prior to the name.

2.2 DomoRules Tool

SWRL is based on OWL ontology language, more

specifically on the OWL-DL branch. It is a language

able to build up rules to perform reasoning about the

instances of an OWL ontology (OWL Individuals)

and infer new knowledge about them.

DomoRules is a tool developed in Java that

facilitates the creation of SWRL rules throughout

API SWRLFactory. It provides a graphic interface

appropriate to assist in the construction of these

rules. It allows obtaining from OntoDomo all the

necessary elements to build a SWRL rule (classes,

instances, properties), to use SWRL variables and

system variables that refer to the values defined by

the user and finally to add SWRL language built-ins

to the rules.

With DomoRules we seek to build SWRL rules

easily without knowing the syntax of this language.

All the elements constituting OntoDomo.owl

ontology are introduced to the user in the interface,

so that, by simply choosing a class or an instance, all

the properties it has will be listed and the user will

be able to pick the one he/she needs and establish its

values in order to build the rules.

DomoRules is born aiming to offer the user a

simple SWRL rules creating application. The task of

designing an intuitive interface to abstract the

SWRL language user is not easy because SWRL is a

powerful language with a very rich vocabulary that

provides high interaction with all its elements.

Accordingly, by using DomoRules the user will be

able to produce rules that shape the system

behaviour that could be used by IntelliDomo.

Figure 2: DomoRules creation rules interface.

2.3 IntelliDomo Module

IntelliDomo is the main control module of the

system using the represented elements and the

different modules which constitute the system. The

information about configuration and location of the

system can be observed graphically on a plan and,

when the state of a device changes, a message alerts

appearing upon the device icon. At the same time

these events happen, it stores a set of log files where

each of the actions carried out by the system and all

the inferences it makes are detailed. It uses the

DBConnection module to get connected to the

different databases that constitute the application,

which can be either DomoBD or the private

databases IntelliDomo uses to store its own data.

3 CONCLUSIONS AND FUTURE

LINES

Ontologies provide an appropriate kind of

representation for identifying types and

characteristics of domotic devices. Furthermore,

production rules expressed in SWRL language allow

establishing relationships among these domotic

devices to shape the integral behaviour of a domotic

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installation.

In the present paper, we introduce IntelliDomo.

On the one hand, it is based on an ontology -known

as OntoDomo- where all types of domotic devices,

together with their useful characteristics, are

represented; and, on the other hand, it is based on

production rules in SWRL language defined

according to the users’ preferences and needs. With

these knowledge bases, IntelliDomo allows

managing the control of the domotic system itself.

The state of the elements that comprise a determined

domotic installation is continuously read from the

database where its values are stored and translated

into instances of OntoDomo ontology. With this

information, together with the rules defined by the

user, IntelliDomo’s inference engine would fire the

appropriate rules that will change the state of the

system devices.

In addition to the IntelliDomo control module,

we have developed DomoRules application, which

works as a SWRL production rules generating

wizard. The interface design has been developed

aiming to be simple and intuitive for every user. As

a result, the user may only select the type of

component (a concrete physic component in the

system) and the appropriate values to build the

condition of the rule antecedent (body).

Nevertheless, we are inclined to provide

IntelliDomo with a learning module where

production rules would be modified according to the

historical procedure of the users. The intention is

that, meanwhile the user interacts with the system or

some determined values are obtained under certain

conditions, the rules can change or their execution

precedes other rules. Therefore, once the user has

established the reasonable importance of behaviour

aspects, rules can be modified in order to adapt the

system behaviour according to the importance of

these criteria.

ACKNOWLEDGEMENTS

This work has been developed under support of

Junta de Extremadura Project (PDT08A023)

REFERENCES

Horrocks I., Patel-Schneider P., Boley H., Tabet S.,Grosof

B., and Dean M. SWRL: A semantic web rule

language combining OWL and RuleML.

http:// www.w3.org/Submission/2004/SUBM-SWRL-

20040521/, Mayo 2004.

Sommaruga, L.; Perri, A.; Furfari, F.; DomoML-env: a

ontology for Human Home Interaction. Proceedings

of SWAP (2005)

Furfari, F.; Sommaruga, L.; Soria, C.; Fresco R.

DomoML: the definition of a standard markup for

interoperability of human home interactions.

Proceedings of the 2nd European Union symposium

on Ambient Intelligence (2004)

Bonino, D.; Corno, F.; Dogont-ontology modeling for

intelligent domotic environments. 7th International

Semantic Web Conference (2008) pp. 790-80

Hepp, M.; De Leenheer, P.; de Moor, A.; Sure, Y. (Eds.)

Ontology Management. Semantic Web, Semantic

Web Services, and Business Applications,

Vol. 7.Springer 2008

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