Active Systems Decisions Enhancement Using User Model in PervasiveComputing Environments

Codruta Ancuti', Cosmin Ancuti', Karin Coninx'Expertise Centrefor Digital Media

Hasselt University- transnationale Universiteit LimburgWetenschapspark 2

B-3590 Diepenbeek, Belgium[codruta. ancuti, cosmin. ancuti, karin. coninx] @ uhasselt. be

Abstract. The knowledge about the user with permanent patient monitoring state, withexpectations and goals increase the effectiveness critical importance, while eHome assures a highof system reaction to detected context. We grade of persons comfort and context basedpresent an analysis of the setting process by situation control functions.meaning building a user model for automatic A general system response in pervasiveprogrammed responses of complex systems. environments must be adaptive to enquiringHowever such step is not an easy task for entities. The same system can be enquired bycommon users. Human logic is a process based machines or humans and ideally will be capableon experiences and implicates a grade of of responding on different defined modalities.uncertainty of values meaning, while computers The automatic system behavior is the basiccan deal only with definite state of situations. connector part of an active environment. TheThe natural language is a challenge approach to advantage of an active system over passiveexplicitly set the system reactions chain for complex embedded systems equipped withcomplex and diverse pervasive systems. Our sensors and remote controllable devices is ofdesign of the system architecture is defined in immediately evidences. A passive embeddedterms of OSGi components but is also applicable system permits users immediately control fromfor different collaboration mode design. We any point. While passive systems goals aremake use of the fuzzy logic to build up connectivity and availability, the active systemscorrelations interpretation with more tangible are designed to fulfill the environment goal.human approach in our process that defines the Our software system design [8] is realizeduser model. using OSGi [9][6] components that assure the

generality connectivity between services variety.Keywords: User Model, OSGi, Pervasive We make use of user model [12] to store the userComputing, User Interface, Fuzzy Logic. acquired knowledge of the system.

The remainder of this paper is structured as

1. Introduction follows: we continue with an overview of theused methodologies in section 1.1 and 1.2. Next,

Nowadays, general tendencies are to sustain we present the system action scheme and a casedevices communication and functionalities of study of a possible scenario that concludes thecollaboration through various techniques. motivation of the chosen techniques. In sectionAutomated ambient environments [2] implicate 2.2 we introduce the data representation and inreliable and intuitive mode to use their 2.3 the interpretation modalities. In 2.4 we

possibilities. discussed the decision-making modeling andIt is of great significance that pervasive then we present a brief overview in section 2.5.

computing environments are built on flexible Finally we draw the conclusions and write downarchitectures and required an intuitive the future work.configuration modality of system functionalities . .with tools to guarantee maximal user 1.1 User Model and acquiring methodssatisfaction. Each pervasive computingenvironment [1] [16] has a various number of The definition of user model [12] iscomplicated problems of fundamental contextual adapted, and a commonly view-pointimportance that must be analyze apart. As is a support to cognizance-based models.ilutaieeapeeeat*niomn el A user model is the knowledge about the user,

acquired and encoded either explicitly or

1-4244-1 326-51071$25.OOI©B2007 IEEE 316

implicitly, that is used by any software to doors). The heterogeneous communicationimprove the interaction modalities. protocols as WiFi or ZigBee have

There are two known modalities to assemble correspondence support. In [8] we havethe information of a user model: explicitly and presented the general design of our built system.implicitly modality. Our prototype persona, Andrew, is explicitly

User models are explicitly built by leading the providing the schedule of desired activities thatuser through a setup process. The user must can be automatically handle by the active system.choose the preferences that are valid for some These data are stored in its user modelcontext. Depending by context situation a user preferences encoded in RDF [5] schema. Thecan choose different models. eHome takes care for him to start the coffee

Implicitly acquiring modality implicates a machine, the toaster and to start and tune the TVchallengeable task, and a complicate reasoning on preferred channel at precise hours. Implicitlymechanism. It is realized by registering the user acquisition of data is not al the time easy toactions and by extracting patterns. motivate. A simple problem of reasoning: in real

life his wife Lisa can't say for sure which meal1.2 Why using OSGi ? menu Andrew could desire for dinner. She is

cooking something that she believes he will likeOSGi is a middleware dedicated for to eat, or what she actually wants for herself. If

interconnected and service based systems. The the system must order from cateringOSGi specifications [9] [6] have been proved to automatically, which menu must request? Thebe valuable building stones for modular systems. measure of believe can be acquired implicitly bySome of the most important characteristics that observing user daily behavior. Still peoplesupply most of the system requirements are: preferences and behavior is most of the time- Dedicated for networked applications and context dependent. The dissatisfaction is always

service-oriented software. greater if a reaction is faulty realized than if no- The update of services can be done at run action was performed.

time over the network. The benefits of active systems are found on- The services can be adapted according to the energy saving and emergency situation detection.

device/user requirements (e.g. mail service, Depending by the weathercast an eHome activeSMS service). system will manipulate the HVAC system with

regards to preferences and users models2.1 Scenario overview schedule.

In an emergency situation as fire detection anFor a faster presentation of the software eHome active system can be set-up to turn off

design motivations we are describing two cases the gas alimentation, make an automatic call tofrom the scenarios we have analyzed. emergency stations, and unlock doors to offer a

In the active set environment of eHome there fast access to fire-fighters. For these context [14]are habiting a couple young family, Andrew and cases the passive role is a regarded as error.Lisa, and their 4 years old boy Jan. Their The simplified action scheme (figure 1)working day schedules are different. Andrew is shows the execution logic steps of the system.going early in the morning at 7:30 o'clock atwork while Lisa is bringing the kid to school at Ss S Monitoring8:30 and then she's going at her work. Andrewlikes to have coffee and fresh toast bread at firstour when he gets awake and to hear sport news 2213 (during that. Because he's awaking hardly, and hespends time on reviewing schedules for that day tTranisfoai User Modemeeting's he was often asked Lisa for breakfast CAserving. After eHome installation, our scenario Con1text Bu1ildei Context definitionturns on this way. The system unit is connected Execution Unitand acquires data from sensors (humidity,temperature, illumination, gas, smoke, etc.), Syte acivrctioncontrols different programmable devices (camera Fig. 1 System reaction schemesurveillance, washing machine, TV) and turnson/off switchers (power supply, water, gas,

317

We have selected some main questions and topology hierarchy. RDF is W3C standard basedwe have started to build our design around them: on XML and was introduced with the scope tohow is defined intelligence reaction, how context facilitate a common way to present and describeis identify, what are the possibilities for user information so these can be read and understoodinteraction. by computer applications. It is a related concept

The intelligence of software is mostly for semi-structured data [11], with applicationsdependent by its dedicated domain. In this on web resources database [4], in data integrationspecific case our system reaction can be regarded [3] and transformation [15]. Any kind of dataas intelligent and makes the system active, if that can be represented as a graph is called semi-fulfills the environment goals, meaning that can structured data.take decisions based on context detection and In figure 2 is presented the constructed databased on user preferences. Our system is model. Using RDF schema the information isacquiring implicitly the context [7] by settings semantically modeled by statements with subject,that are assigned to user models. predicate and objects. The environment context

Providing user preferences to system is is represented by objects in the environmentsimilar with man-machine dialog and for user ontology. Instants values of temperature,with general knowledge is proven to found rather humidity, illumination are different environmentcomplicate the setup steps. information that system is processing for

Because the system actions are based on deploying context based actions.context implicit description, making these The user model contains data as uniqueappropriate to deal with for most users is of great identifier, name, rights, and rules. The set ofimportance. The following chapter is describing rights contain the user access rights to devicesthe approach for dealing this aspect. and services. The set of rules contain the context

constrains and the actions that are performed as2.2 Decision mechanism and data topology automatic system modality to react. More

explanations about the rules building process areUsually the setting steps for automatic system in the following subchapter.

decisions and behavior are a complex process We present in this paper a tool design thatwhich is most of the time realized by technical will permit to non technical persons to programpersons. based on accumulated experience or preferences

Modeling the decision-making modality in the system reaction when defined context casesthe reasoning process is one step closer to human occurs. We use fuzzy logic [10] because itinterpretation of data. These implicates in our efficiently modulates mathematical situationscase that users can choose the triggering with a degree of certainty and because it makesconstrains and the chains of reactions for defined use of values linguistic interpretation. Reasoningcontext situation. mechanism in a simplify mode can be resumed

The knowledge representation of user goals on identifying actual context situation operationand actions preference (figure 2) is essential for that triggers the system actions. This response iscorrect functioning systems based on user model. extracted from user model data provided in the

haslE rUs Admin system setup and calibration steps.i hasNane HasRightf has ule,i0 admin 2.3 User preferences interpretation

Rights admin RulesadmmodalitieshasDevices as erviceE hasConstrains ha tior

Devices al srieConstr3inato

haslSservcehSitf hasTime sEeenl hRelati The main difficulties for most of users thathasEElementtsFT<7 ,Ie al,0 , thasElements fnlu deals with decision-making system programming1923160(~FlfEand lements

rlEementsEs entilato remain the large number of parameters and thetemeraur um has atterns vast values ranges with their significances.

hasPatterns hasPatterns Human language is representing real values with

Fuzzy sel (twarw) nOrattserltteowt linguistic interpretation. Reviewing the fact thathasProbabilits hasPjobabilits hasProbabiIit- these systems are designedforhuman

Membership grade 0306 0 manipulation, a more suitable solution is thatFig.2 User data model capable to deal with linguistically representation

We are using Resource Description Of the values.Framework (RDF) [5] model for building data

318

A significant drawback of the complex light situation to its own sensation and thepervasive systems is the lacks in adaptation of accumulated knowledge about the other personthe settings to the user preferences. There is not a preferences and sensibility.simple way to realize this, because people are The problem becomes complicated tosubjective and theirs believes or trust degree interpret if the light intensity is a case ofmay vary from totally unfounded till totally classification variable. Instead of just turning thefounded. The natural language system must light on or off the system must appreciate therecognize the bias factor for a correct expected percent that the user is required. Thiscommunication. simple given example case is still manageable

The system settings behavior is storing the with no complex decision implementation.chains of actions that are executed when some The necessity of modeling expertcertain events are produced. Often these system knowledge's is illustrated by eHealthsettings process are dealt by specialized environment. This implicates monitory functionstechnicians. They are tailoring the system which must be adapted for each patient by thepossibilities to the user expectations. Any further medical personal. For example if a heart tensionmodifications with no high significance on the value of 100/160 is going to be considered asgeneral reaction is hard to manage by users threshold as problematic, and requiring attention,because the system was built that way that the the logic experienced based on human decisionautomatic behavior is not easy to handle. More can decide that also 95/155 is also closed to theover, the user preferences before the actually situation. More over if a person has otherinstallation and after some trial period are not diseases the threshold will correspond to othermatching and need readjustments. Users that adjusted values.have indeed the possibility to control intuitive Using values ranges to classify values is aand directly their devices in such environments, very fast and straightforward process for buildingwhile the automatic response remain not entirely up the application. This is often managed usingprogrammable, and so with a lack of utility, will decision trees programming approach to dealnot be satisfied completely. with the classification. The main disadvantage is

In our daily activities we interpret real values that the distribution of values into the rangeswith linguistic terms that illustrate and classify provides no certainty about information. In realthe situation status based on believes. Pervasive world human use a linguistic term with ansystems that are designed for human interaction implicit grade of imprecision named cognitivewould be less difficult to interact and understand biases [13] related with its personal believes.if the input values represent linguistic values. There are precise values that have differentThe final goal of implicit communication is to correspondences for different persons and a veryfacilitate system programming by normal users. good example is temperature. A Swedish personA very simple example is: turn the lights ON can find 10°C outside as warm, while a Spanish

when the light intensity is under some values. A person can find it cold. The value of certaintyvalue of 5.7657 says nothing to a non-specialized must be regarded also as an important factor inperson. Even more each sensor has specific range software decisions.and characteristics curves of data model, which A more appropriate transformationmakes the setup process harder also for correlation from values into language terms musttechnicians. A value as light on and light off are be related with the certainty grade of truth.easy to interpret by common users, but also Describing expert system that supportsseriously reduces the system functionality language values input and certaintycomplexity. representations is straight forwards to be

Combination of more then 2 factors is most of implemented by using fuzzy logic approach.the time hard to be realized by users especially if Fuzzy logic deals with sets. A set can be seen asthey aren't often confident that their logic a collection of objects that can be treated as aconditions are correctly, when values are not whole. The mathematician Georg Cantorcommonly easy to interpret. described a set by its members, such that an item

Definition of the commands as: "turn the from a given universe is either a member or not.lights on when the person can 't see well" are The terms set, collection and class are synonyms,hard to put in practice for most of the systems. just as the terms item, element and member. LotfiFor a human assistant this case is straight Zadeh the pioneer of fuzzy logic (1965, 1973,forward to realize it. He is reporting the cuffent 1975), claimed that many sets in the world that

319

surrounds us are defined by a non-distinct accumulated experience the input parametersboundary. Zadeh decided to extend two-valued values in environment context.logic, defined by the binary pair {0, II to the Context definition implicates the answers towhole continuous interval [0, 1] thereby the considered questions [7] that complete anintroducing a gradual transition from falsehood image about the actual situation: who - sensorto truth that contains as special case the pair {0, information, where - spatial location, what - real1}. This value represents the membership grade value, how - user interpretation.into a set for each element. Setting the output values once the context is

identified and classified is the second step on2.4. Execution and decision steps setting process.

The decision process is described by usersOur developed eHome system is built on and is built up human. The primary functionality

OSGi middleware. The concept is services is to create the correlation relations matrix.collaboration in an open multilayer architecture.The main idea of the collaboration is to realize aclear distinction between the different tasks of 2.5 Fuzzy logic fundamentals overviewthe system while avoiding the rigidity of layeredsystems where only the direct previous layer can Fuzzy logic methodology [10] is modelingbe accessed. many decision-making problems situations in anWe make use of a mobile agent to deploy appropriate way to the human perception.

flexible and adaptable user interfaces on different Commonly in real world these situations are notdevices with limited resources (PDA, GSM, and one hundred percent true or false. This is theiDTV). Our developed mobile agent is capable to reason why many control and decision-makingadapt the user interface to devices interaction problems do not easily fit into the strict true/falsepossibilities. situation required by mathematical modes.We present in this paper the concept design Fuzzy expert systems and are not widely used

for a tool that aims to easier the settings process but the most common use of them is in severalof the automatic behavior of the system. As wide-ranging fields that include linear andalready presented it makes use of logic decision- nonlinear control, pattern recognition, financialmaking correspondence between triggering systems, and data analysis.context and the action. This is designated for non The model of execution is synthesizedtechnical users. through 3 stages: the fuzzification process, rule

The correlation between linguistic values and evaluation and defuzzification process. Therepresentation range is a complicate and a hard fuzzification comprises the process ofproblem to be managed by most of the persons. transforming crisp values into grades ofThis correlation process implicates a correct membership for linguistic terms of fuzzy setsapproximation of the linguistic terms. It requires (presented in interpretation modalitiesa good experience, and so this part is advisable to subchapter). The membership grade can havebe tuned by technicians or by imposing values from 0 to 1 where 1 means that the valueconfiguration standards. A significant fact is that belongs to the set and 0 is the opposite. Theonce is set the correspondence pairs, these can be deffuzification is the reverse of fuzzificationused in the setting process. process.

Rule evaluation interprets:Who Where What When How if ( conditions) then ( actions)Sens Temp bedroo i 43322 1522 coldand specific for our case of study,

SensTempibedromi 4332 152 cold conditions are built around context build andI I I ~~~~~~~sothe actions.Sens Humid bedroom 6565 15 22 norma

3. Conclusions and future workContext Fuzzy Logic lUserModel

We intend to build e-health home center usingVetlao poe bero 0 1 22NPoe a services oriented open multilayer architectureFig.3 Contextbased decision built on OSGi. The system extends the already

Building up the table of automatic actions is developed ehome environment functionalitiesbased on connecting logically and based on

320

and adds the novelty of more specialized [4] J. Hammer, J. McHugh, H. Garcia-Molina:functions. Semistructured Data: The TSIIMMIS

Designing an appropriate tool to support in Experience. In Proceedings of the Firstpervasive computing environments an intuitive East-European Workshop on Advances inand efficient manipulation from the user of the Databases and Information Systems-ADBISconditions and the expected settings results, '97, St. Petersburg, Russia, September 1997.depends strongly on capacity to expose and to [5] F. Manola, E. Miller (eds.), Resourceinterpret the system features and classify the Description Framework (RDF)parameters values. Our future development work Recommendation, 2004,will evaluate the generalizing system grade and http://www.w3.org/TR /rdf-primer/will analyze the flexibility of the data structure [6] D. Marples, P. Kriens. The Open Servicesrepresentation. Gateway Initiative: an introductoryWe have presented a possible approach for overview. Communications Magazine, IEEE

building automatic system behavior with 2001; 39(12): 110-114.possibility of user implication in the complex [7] T.P. Moran, P. Dourish. Introduction to Thisdecision manipulation process. In our specific Special Issue on Context-Aware Computing.case the e-health environment must react HCI 2001; vol. 16(2): 87-95.automatically and to identify situations that [8] C. Ancuti, M. Fumarola, K. Luyten, K.implicate the patient health state monitoring. Coninx, S. Palmaers, N. Eichmann, F.

Using this presented method we intend to Vos, General Adaptable Servicesdevelop tool interface that set the automatic Manager for Pervasive Systems,system reactions based on user preferences or its accepted on IT12007.cumulated expertise. [9] OSGi Alliance About the OSGi Service

Our researching efforts are focused in future Platform, Technical Whitepaper; 2005.http:/on enhancement the context-aware modalities www.osgi.org/from implicitly to explicitly based on multi- [10] Pearson, Fuzzy Logic Fundamentals, 2001.modal interaction human-computer interactions. [11 ]Peter Buneman: Semistructured Data.

Proceedings of the Sixteenth ACMSIGACT-SIGMOD-SIGART Symposiumon Principles of Database Systems 1997:

The OCoMIS research project was funded by 17 -121.the Flemish Government through the IWT- 117.121the FemishGovermentthrouh the1WT- [12] Robert Klass, Tim Finin, Modeling the userFlanders. We also wish to thanks our industrialpartners, for their valuable feedback. in natural language system, Journal:

partnes ofo theresearchvaluable feedbk iComputational Linguistics, MIT Press, 3(14)Part of the research at EDM iS funded by 5-22.ERDF (European Regional Development Fund), [ A v a nethe Flemish Government and the Flemis [13] Amos Tversky and Daniel Kahneman:IntherdisFpleishr Government and theoFlemh Judgment under Uncertainty: Heuristics andInTerdiscipolinay insBTitute for Broad-Band Biases, Science, 27 September 1974, vol.Technology (IBBT). 1 85: 1124-1131.

5. References [14] Thomas P. Moran, Paul Dourish:S.References Introduction to This Special Issue on

I]W.S. Ark, T. Selker. A look at human Context-Aware Computing, Contents of[1] interk, Th per. comput IBm HCI vol. 16 (2001), 2001, Vol. 16, No. 2, 3interaction with pervasive computers. IBM & 4:87-95.

Syst. J. 1999; 38(4): 504-507.&4895Syt.. '19 384) 504-507. [15] Serge Abiteboul, Sophie Cluet, Tova Milo:[2]D. Cook, S. Das. Smart Environments: Cofsonec an Trnlto. oTehooy Prtcl and Applcaton. Correspondence and Translation forTechnology, Protocols and Applications. Heterogeneous Data. ICDT 1997: 351-363.

Wiley-Interscience; 2004.[3] H. Garcia-Molina, J. Hammer, K. Ireland, Y [16]FM. Weser. The Computer for the Twenty-

Papakonstantinou, J. Ullman, J. Widom: First Century. Scientific American 1991;Integrating and Accessing Heterogeneous ( 9Information Sources in TSIIMMIS.Proceedings of AAAI Spring Symposiumon Information Gathering, 1995.

321