An approach to improve semantics in

Smart Spaces using reactive fuzzy rules

Natalia Díaz Rodríguez & Johan Lilius Turku Centre for Computer Science (TUCS),

Åbo Akademi University, Turku, Finland M.P. Cuéllar & Miguel Delgado Calvo-Flores

University of Granada, Spain

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IFSA World Congress - NAFIPS 2013, Edmonton, Canada 25.6.13

Introduction

§  Smart Spaces (UbiComp): interoperability, working on behalf of the user, handle unanticipated situations

§  Human behaviour modelling: crucial task in AmI environments

§  Problem: Sensor data as crisp events.

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Introduction

§  Context-awareness for machine processing and reasoning.

§  Semantic Technologies and Ontologies:

Independent knowledge sharing minimizing redundancy.

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Related Work: fuzzy reasoners

Related Work: architectures

§  Different semantic storage solutions, some fuzzy extensions of SPARQL (e.g. F-SPARQL).

§  What is missing? An integrated single solution supporting: – W3C standards (RDF, OWL, SPARQL). – RDF stores with support for efficient and real-time

pub/sub event notifications. – Uncertain, imprecise expressions.

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Our proposal: A hybrid framework for context-aware Smart Space application development

2 main components: Crisp KB and Fuzzy KB, connected by a rule engine which handles each type of event subscriptions. a.  CRISP element: SPARQL Subscription-based RDF store with

Pub/Sub architecture: Smart-M3 b.  FUZZY element: Expressive Fuzzy DL reasoner, allows

mapping to a fuzzy control system: fuzzyDL

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Fuzzy KB and rules in fuzzyDL

Fuzzy KB and rules in fuzzyDL

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Hybrid architecture proposal with fuzzy and crisp KBs

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Equivalent queries to be executed in both crisp M3 and fuzzyDL KBs

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Mapping of rule antecedent “IF Natalia hasStatus AwayForWeekend” to SPARQL and fuzzyDL queries.

Mapping of subscription pattern types to fuzzyDL queries

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Conclusions

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§  Hybrid Fuzzy-Crisp architecture whose –  Quantitative (SPARQL, event Pub/Sub) and Qualitative

(semantics + fuzzy reasoning expressive power) views allow a versatile framework for developing Smart Space applications.

–  strategy allows loosening of semantics or efficiency (depending on application needs): avoiding continuous querying for changes or fuzzy discretization-based solutions.

–  Knowledge representation & queries are + flexible §  fuzzyDL still does not support some required semantic constraints §  2 KBs = Redundancy (twofold updates) -> advantage for

optimizing execution time of different queries/ datasets

Future Directions

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§  Rule serializers (for crisp and fuzzy architectures) §  Scalability + performance experiments in real-life applications

(reasoning, querying/updating and subscription response VS ontology size & fuzzy/crisp/hybrid rules)

§  Optimization: Semantic generalization of hybrid antecedents 1.  When strict semantics are to be preserved (we sacrifice

performance): –  IF (WeatherSituationTurku, isCurrently, VeryStormy) –> IF (WeatherSituationTurku, isCurrently, ?).

2.  Transforming patterns into crisp-only (sacrifices semantic precision): –  IF(Natalia, isVeryNearTo, JohansOffice) –> IF(Natalia, isNearTo,

JohansOffice).

Future Directions

§  Pub/sub fuzzy reasoner (->Fuzzy SPARQL?) §  Alternatives to data redundancy keeping

consistency? §  Overall: Standardization of fuzzy SPARQL extension for fuzzy reasoning will achieve more usable, flexible, personalized and adaptive Smart Spaces

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Thank you for your attention!

Natalia Díaz Rodríguez ndiaz@abo.fi

Embedded Systems Lab. Department of Information Technologies Åbo Akademi University, Turku, Finland

TUCS (Turku Centre for Computer Science)

Department of Computer Science and Artificial Intelligence University of Granada, Spain

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