Personal and Ubiquitous Computing

, Volume 16, Issue 7, pp 781–797 | Cite as

Design and validation of a light inference system to support embedded context reasoning

  • Josué Iglesias
  • Ana M. Bernardos
  • Paula Tarrío
  • José R. Casar
  • Henar Martín
Original Article

Abstract

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.

Keywords

Context-aware application Data modelling Light ontology management Embedded reasoning Service-oriented architectures Activity inference 

Notes

Acknowledgments

This work has been supported by the Spanish Ministry of Industry, Tourism and Commerce and the European Fund for Regional Development under grant TSI020301-2008-2, the Ministry for Science and Innovation under grant TIN2008-06742-C02-01 and the Government of Madrid under grant S2009/TIC-1485. The authors also acknowledge enriching discussions with Marcos Sacristán and Alejandro Álvarez of the PIRAmIDE project.

References

  1. 1.
    Baldauf M, Dustdar S, Rosenberg F (2007) A survey on context aware systems. Int J Ad Hoc Ubiquitous Comput 2:263–277CrossRefGoogle Scholar
  2. 2.
    Perttunen M, Riekki J, Lassila O (2009) Context representation and reasoning in pervasive computing: a review. Int J Multimed Ubiquitous Eng 4(4):1–28Google Scholar
  3. 3.
    Gu T, Pung HK, Zhang DQ (2004) Toward an osgi-based infrastructure for context-aware applications. IEEE Pervasive Comput 3:66–74Google Scholar
  4. 4.
    Chen H, Finin T, Joshi A (2004) Semantic web in the context broker architecture. In: Proceedings of the second IEEE international conference on pervasive computing and communications (PERCOM‘04), Orlando, Florida, USA, Mar 14–17, 2004, IEEE Computer Society, Washington, pp 277–286Google Scholar
  5. 5.
    Fahy P, Clarke S (2004) Cass: a middleware for mobile context-aware applications. In: Proceedings of the workshop on context awareness (MobiSys’04), Boston, Massachusetts, USA, June 6–9, 2004, pp 1–6Google Scholar
  6. 6.
    Chan ATS, Chuang SN (2003) Mobipads: a reactive middleware for context-aware mobile computing. IEEE Trans Softw Eng 29:1072–1085CrossRefGoogle Scholar
  7. 7.
    Kleemann T (2006) Towards mobile reasoning. In: Parsia B, Sattler U, Toman D (eds) CEUR workshop proceedings on description logics, vol 189, Lake District, UK, May 30–June 1, 2006, CEUR-WS.orgGoogle Scholar
  8. 8.
    Toma E, Simperl GH (2009) A joint roadmap for semantic technologies and the internet of things. In: Workshop proceedings of the 3rd STI roadmapping workshop charting the next generation of semantic technology at the 6th European semantic web conference (ESWC 2009), June 1, 2009, Heraklion, GreeceGoogle Scholar
  9. 9.
    Bettini C, Brdiczka O, Henricksen K, Indulska J, Nicklas D, Ranganathan A, Riboni D (2010) A survey of context modelling and reasoning techniques. Pervasive Mob Comput 6:161–180CrossRefGoogle Scholar
  10. 10.
    Strang T, Linnhoff-Popien C (2004) A context modeling survey. In: Workshop on advanced context modelling reasoning and management as part of UbiComp, Nottingham, UK, Sept 9, 2004, pp 1–8Google Scholar
  11. 11.
    Beigl M, Gellersen H (2003) Smart-its: an embedded platform for smart objects. In: Proceedings of smart objects conference (SOC’03), Grenoble, France, May 15–17, 2003, pp 15–17Google Scholar
  12. 12.
    Siegemund F (2004) A context-aware communication platform for smart objects. In: Ferscha A, Mattern F (eds) Proceedings of the international conference on pervasive computing (PERVASIVE’04), vol 3001, Linz, Viena, April 18–23, 2004, ser. LNCS, Springer, Berlin, pp 69–86Google Scholar
  13. 13.
    Corredor I, Martínez JF, Familiar MS (2011) Bringing pervasive embedded networks to the service cloud: a lightweight middleware approach. J Syst Archit Embed Softw Des (To appear), Special Issue: Emerging applications of embedded systems, ElsevierGoogle Scholar
  14. 14.
  15. 15.
    Knappmeyer M, Kiani SL, Fra C, Moltchanov B, Baker N (2010) Contextml: a lightweight context representation and context management schema. In: Proceedings of the 5th IEEE international symposium on wireless pervasive computing (ISWPC’10), Modena, Italy, May 5–7, 2010, IEEE Press, Piscataway, NJ, USA, pp 367–372Google Scholar
  16. 16.
    Ye J, Coyle L, Dobson S, Nixon P (2007) Ontology-based models in pervasive computing systems. Knowl Eng Rev 22:315–347CrossRefGoogle Scholar
  17. 17.
    SOPRANO: Service oriented programmable smart environments for older Europeans (2007) Deliverable D1.1.2: review state-of-the-art and market analysis, Version 1.1Google Scholar
  18. 18.
    Boury-Brisset AC (2003) Ontology-based approach for information fusion. In: Proceedings of the sixth international conference of information fusion, Cairns, Queensland, Australia, July 8–11, 2003, International Society of Information Fusion, vol 1, pp 522–529Google Scholar
  19. 19.
    OWL Web Ontology Language Overview (2004). http://www.w3.org/TR/owl-features/
  20. 20.
    Spyns P, Meersman R, Jarrar M (2002) Data modelling versus ontology engineering. SIGMOD Rec 31(4):12–17CrossRefGoogle Scholar
  21. 21.
    RDF/XML Syntax Specification (2004). http://www.w3.org/TR/REC-rdf-syntax/
  22. 22.
    Su X, Riekki J (2010) Transferring ontologies between mobile devices and knowledge-based systems. In: Proceedings of the 2010 IEEE/IFIP international conference on embedded and ubiquitous computing (EUC‘10), Hong Kong, China, Dec 11–13, 2010, IEEE Computer Society, pp 127–135Google Scholar
  23. 23.
    Horridge M, Drummond N, Goodwin J, Rector A, Wang HH (2006) The Manchester owl syntax. In: Proceedings of the OWL experiences and directions workshop (OWLED), vol 216, Athens, Georgia, USA, Nov 10–11, 2006, CEUR-WS.orgGoogle Scholar
  24. 24.
    Koziuk M, Domaszewicz J, Schoeneich R, Jablonowski M, Boetzel P (2008) Mobile context-addressable messaging with dl-lite domain model. In: Roggen D, Lombriser C, Trster G, Kortuem G, Havinga P (eds) Smart sensing and context (lecture notes in computer science), vol 5279. Springer, Heidelberg, pp 168–181Google Scholar
  25. 25.
    Schneider PP, Swartout B (1993) Description-logic knowledge representation system specification from the KRSS group of the ARPA knowledge sharing effortGoogle Scholar
  26. 26.
    Kleemann T, Sinner A (2005) Description logic based matchmaking on mobile devices. In: Baumeister J, Seipel D (eds) Proceedings of 1st workshop on knowledge engineering and software engineering (KESE’05), Koblenz, Germany, Sept 11, 2005, pp 37–48Google Scholar
  27. 27.
    RDF Test Cases (2004) W3C Recommendation. http://www.w3.org/TR/rdf-testcases/#ntriples
  28. 28.
    Cuenca B, Motik B, Wu Z, Fokoue A (2008) OWL 2 web ontology language: profiles. W3C Working DraftGoogle Scholar
  29. 29.
    Crivellaro F (2007) microJena: Gestione di ontologie sui dispositivi mobile. M.Sc. Thesis, Politecnico di MilanoGoogle Scholar
  30. 30.
    Carroll JJ, Dickinson I, Dollin C, Reynolds D, Seaborne A, Wilkinson K (2004) Jena: implementing the semantic web recommendations. In: Proceedings of the 13th international world wide web conference on alternate track papers & posters, (WWW Alt.’04), New York, NY, USA, May 17–22, 2004, ACM, New York, pp 74–83Google Scholar
  31. 31.
    Sinner A, Kleemann T (2005) Krhyper in your pocket. In: Nieuwenhuis R (ed) Automated deduction CADE-20 (lecture notes in computer science), vol 3632. Springer, Heidelberg, pp 452–457CrossRefGoogle Scholar
  32. 32.
    Horrocks I, Patel-Schneider PF, Boley H, Tabet S, Grosof B, Dean M (2004) SWRL: a semantic web rule language combining OWL and RuleML. W3C member submissionGoogle Scholar
  33. 33.
    Gu T, Kwok Z, Koh KK, Pung HK (2007) A mobile framework supporting ontology processing and reasoning. In: Proceedings of the 2nd workshop on requirements and solutions for pervasive software infrastructures (RSPSI‘07), in conjunction with the 9th international conference on ubiquitous computing (Ubicomp’07), Innsbruck, Austria, Sept 16–19Google Scholar
  34. 34.
    Ali S, Kiefer S (2009) Micro a micro owl dl reasoner for ambient intelligent devices. In: Abdennadher N, Petcu D (eds) Advances in grid and pervasive computing (lecture notes in computer science), vol 5529. Springer, Heidelberg, pp 305–316CrossRefGoogle Scholar
  35. 35.
    Vazquez Gomez JI (2007) A reactive behavioural model for context-aware semantic devices. Ph.D. thesisGoogle Scholar
  36. 36.
    Jang M, Sohn JC (2004) Bossam: an extended rule engine for owl inferencing. In: Antoniou G, Boley H (eds) Rules and rule markup languages for the semantic web (lecture notes in computer science), vol 3323. Springer, Heidelberg, pp 128–138CrossRefGoogle Scholar
  37. 37.
    Boley H (2006) The RuleML family of web rule languages. In: Alferes J, Bailey J, May W, Schwertel U (eds) Principles and practice of semantic web reasoning (lecture notes in computer science), vol 4187. Springer, Heidelberg, pp 1–17CrossRefGoogle Scholar
  38. 38.
    Tramp S, Frischmuth P, Arndt N, Ermilov T, Auer S (2011) Weaving a distributed, semantic social network for mobile users. In: Proceedings of the 8th extended semantic web conference (ESWC’11), Heraklion, Greece, May 29–June 2, 2011. Springer, Heidelberg, pp 200–217Google Scholar
  39. 39.
    Toninelli A, Pathak A, Issarny V (2011) Yarta: a middleware for managing mobile social ecosystems. In: Riekki J, Ylianttila M, Guo M (eds) Advances in grid and pervasive computing (lecture notes in computer science), vol 6646. Springer, Heidelberg, pp 209–220CrossRefGoogle Scholar
  40. 40.
    Specht G, Weithoner T (2006) Context-aware processing of ontologies in mobile environments. In: Proceedings of the 7th international conference on mobile data management, MDM 2006, Nara, Japan, May 9–13, 2006, IEEE Computer Society Washington, DC, USA, pp 86–89Google Scholar
  41. 41.
    Kofod-Petersen A, Aamodt A (2003) Case-based situation assessment in amobile context-aware system. In: University des Saarlandes (ed) Proceedings of artificial intelligence in mobile systems (AIMS’03), Seattle, WA, USA, Oct 12, pp 41–49Google Scholar
  42. 42.
    Raento M, Oulasvirta A, Petit R, Toivonen H (2005) Context-phone: a prototyping platform for context-aware mobile applications. IEEE Pervasive Computing 4(2):51–59CrossRefGoogle Scholar
  43. 43.
    Yamabe T, Takagi A, Nakajima T (2005) Citron: a context information acquisition framework for personal devices. In: Proceedings of 11th IEEE international conference on embedded and real-time computing systems and applications (RTCSA’05), Hong-Kong, China, Aug 17–19, IEEE Computer Society, pp 489–495Google Scholar
  44. 44.
    Vázquez JI, de Ipiña DL, Sedano I (2006) Soam: an environment adaptation model for the pervasive semantic web. In: Gavrilova ML, Gervasi O, Kumar V, Tan CJK, Taniar D, Laganá A, Mun Y, Choo H (eds) ICCSA (4) (lecture notes in computer science), vol 3983. Springer, Berlin, pp 108–117Google Scholar
  45. 45.
    Tai W, Brennan R, Keeney J, O’Sullivan D (2009) An automatically composable OWL reasoner for resource constrained devices. In: Proceedings of the 2009 IEEE international conference on semantic computing (ICSC’09), IEEE Computer Society, Washington, DC, USA, pp 495–502Google Scholar
  46. 46.
    Organization for the Advancement of Structured Information Standards (2006) Reference model for service oriented architecture 1.0. OASISGoogle Scholar
  47. 47.
    Noy NF, McGuinness DL (2001) Ontology development 101: a guide to creating your first ontology. Tech. Rep. Stanford Knowledge Systems Laboratory and Stanford Medical Informatics, Stanford, CA, USAGoogle Scholar
  48. 48.
    Iglesias J, Bernardos AM, Alvarez A, Sacristan M (2010) A light reasoning infrastructure to enable context-aware mobile applications. In: Proceedings of the 2010 IEEE/IFIP international conference on embedded and ubiquitous computing (EUC’10), IEEE Computer Society, Washington, DC, USA, pp 386–391Google Scholar
  49. 49.
    Iglesias J, Cano J, Bernardos AM, Casar J (2011) A ubiquitous activity-monitor to prevent sedentariness. In: Proceedings of the IEEE international conference on pervasive computing and communications workshops (PERCOM’11 workshops), Seattle, WA, USA, Mar 21–25, IEEE, pp 319–321Google Scholar
  50. 50.
    Food and Agricultural Organization of the United Nations, United Nations University, World Health Organization (2004) Human energy requirements: report of a joint FAO/WHO/UNU expert consultation. Rome, 17–24 Oct 2001. FAO food and nutrition technical report series. Food and Agricultural Organization of the United NationsGoogle Scholar
  51. 51.
    Klinov P (2008) Pronto: a non-monotonic probabilistic description logic reasoner. In: Bechhofer S, Hauswirth M, Hoffmann J, Koubarakis M (eds) The semantic web: research and applications (lecture notes in computer science), vol 5021. Springer, Heidelberg, pp 822–826Google Scholar
  52. 52.
    Bobillo F, Straccia U (2010) Representing fuzzy ontologies in OWL 2. In: Proceedings of the IEEE international conference on fuzzy systems (FUZZ’10), Barcelona, Spain, July 2010, IEEE, pp 2695–2700Google Scholar
  53. 53.
    Prud’hommeaux E, Seaborne A (2008) SPARQL query language for RDF. W3C recommendation. http://www.w3.org/TR/rdf-sparql-query/
  54. 54.
    Hori M, Euzenat J, Patel-Schneider PF (2003) OWL web ontology language XML presentation syntax. W3C Note. http://www.w3.org/TR/owl-xmlsyntax/
  55. 55.
    O’Connor MJ, Das AK (2008) SQWRL: a query language for OWL. In: Hoekstra R, Patel-Schneider PF (eds) Proceedings of the 6th international workshop on OWL: experiences and directions (OWLED’09), vol 529, Chantilly, VA, USA, Oct 23–24, Springer, Berlin/HeidelbergGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Josué Iglesias
    • 1
  • Ana M. Bernardos
    • 1
  • Paula Tarrío
    • 1
  • José R. Casar
    • 1
  • Henar Martín
    • 1
  1. 1.Universidad Politécnica de MadridMadridSpain

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