Soft Computing

, Volume 21, Issue 8, pp 2005–2013 | Cite as

A semantics-based approach to multi-source heterogeneous information fusion in the internet of things

Methodologies and Application

Abstract

Multi-source heterogeneous information fusion in the Internet of Things (IoT) is a type of information processing that attempts to provide a comprehensive, timely and accurate perception and feedback relative to physical things. Traditional multi-sensor data fusion can deal with the same type of data effectively. However, as new characteristics emerge in the IoT, interoperable service-oriented technologies are required to share real-world data among heterogeneous devices to integrate and fuse the multi-source heterogeneous IoT data. To address these issues, an architecture that can provide guidance for the development of IoT information fusion is required. We compare features of IoT data and information with an existing wireless sensor network and the Internet, which, to the best of our knowledge, is the first comparison of this kind. Then, we design a framework for multi-source heterogeneous information fusion in the IoT and use an experimental simulation platform to build an environmental monitoring system to assess the framework.

Keywords

Internet of things Heterogeneous information fusion  Semantic sensor network 

References

  1. Barnaghi P, Wang W, Dong L, Wang C (2013) A linked-data model for semantic sensor streams. In: 2013 IEEE international conference on green computing and communications and IEEE internet of things and IEEE cyber, physical and social computing, GreenCom-iThings-CPSCom 2013, 20 August 2013–23 August 2013. Proceedings of the 2013 IEEE international conference on green computing and communications and IEEE internet of things and IEEE cyber, physical and social computing, GreenCom-iThings-CPSCom 2013, pp 468–475. IEEE Computer Society, New York. doi:10.1109/GreenCom-iThings-CPSCom.2013.95
  2. Compton M, Barnaghi P, Bermudez L, Garcia-Castro R, Corcho O, Cox S, Graybeal J, Hauswirth M, Henson C, Herzog A, Huang V, Janowicz K, Kelsey WD, Le Phuoc D, Lefort L, Leggieri M, Neuhaus H, Nikolov A, Page K, Passant A, Sheth A, Taylor K (2012) The SSN ontology of the W3C semantic sensor network incubator group. J Web Semant 17:25–32. doi:10.1016/j.websem.2012.05.003
  3. Evans D (2011) The internet of things: how the next evolution of the internet is changing everything (CISCO white paper). http://www.cisco.com/web/about/ac79/docs/innov/IoT_IBSG_0411FINAL.pdf
  4. Gabrilovich E, Markovitch S (2007) Computing semantic relatedness using wikipedia-based explicit semantic analysis. IJCAI 7:1606–1611Google Scholar
  5. Hasan S, Curry E (2014) Approximate semantic matching of events for the internet of things. ACM Trans Internet Technol 14(1):23 (WOS:000341067000002)Google Scholar
  6. Henson C, Sheth A, Thirunarayan K (2012) Semantic perception: converting sensory observations to abstractions. IEEE Internet Comput 16(2):26–34. doi:10.1109/MIC.2012.20
  7. Hernandez JL, Moreno MV, Jara AJ, Skarmeta AF (2014) A soft computing based location-aware access control for smart buildings. Soft Comput 18(9):1659–1674 (WOS:000340498800002)Google Scholar
  8. Jain P, Hitzler P, Sheth AP, Verma K, Yeh PZ (2010) Ontology alignment for linked open data. In: 9th international semantic web conference, ISWC 2010, 7 November 2010–11 November 2010, vol 6496. LNCS of lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics), pp 402–417. Springer, New York. doi:10.1007/978-3-642-17746-0_26
  9. Jara AJ, Olivieri AC, Bocchi Y, Jung M, Kastner W, Skarmeta AF (2014) Semantic web of things: an analysis of the application semantics for the IoT moving towards the IoT convergence. Int J Web Grid Serv 10(2–3):244–272 (WOS:000334070200006)Google Scholar
  10. Kreibich O, Neuzil J, Smid R (2014) Quality-based multiple-sensor fusion in an industrial wireless sensor network for MCM. IEEE Trans Ind Electron 61(9):4903–4911 (WOS:000333467900047)Google Scholar
  11. Le-Phuoc D, Nguyen-Mau HQ, Parreira JX, Hauswirth M (2012) A middleware framework for scalable management of linked streams. J Web Semant 16:42–51 (Elsevier). doi:10.1016/j.websem.2012.06.003
  12. Nakamura EF, Loureiro AAF, Frery AC (2007) Information fusion for wireless sensor networks: methods, models, and classifications. ACM Comput Surv 39(3):55 (WOS:000249658500003)Google Scholar
  13. Perera C, Zaslavsky A, Liu CH, Compton M, Christen P, Georgakopoulos D (2014) Sensor search techniques for sensing as a service architecture for the internet of things. IEEE Sens J 14(2):406–420Google Scholar
  14. Rinne M, Torma S, Nuutila E (2012) SPARQL-based applications for RDF-encoded sensor data. In: 5th international workshop on semantic sensor networks, SSN 2012—a workshop of the 11th international semantic web conference 2012, ISWC 2012, 12 November 2012. CEUR workshop proceedings, vol 904, pp 81–96. Sun SITE Central Europe CEUR-WSGoogle Scholar
  15. Ryu M, Kim J, Yun J (2015) Integrated semantics service platform for the internet of things: a case study of a smart office. Sensors 15(1):2137–2160 (WOS:000348309400116)Google Scholar
  16. Severini M, Squartini S, Piazza F (2013) Hybrid soft computing algorithmic framework for smart home energy management. Soft Comput 17(11):1983–2005 (WOS:000325822900003)Google Scholar
  17. Strategy I, Unit P (2005) ITU internet reports 2005. The internet of things. ITU internet reports. ITU, GenevaGoogle Scholar
  18. Su X, Riekki J, Nurminen JK, Nieminen J, Koskimies M (2015) Adding semantics to internet of things. Concurr Comput Pract Exp 27(8):1844–1860. doi:10.1002/cpe.3203
  19. Taylor K, Griffith C, Lefort L, Gaire R, Compton M, Wark T, Lamb D, Falzon G, Trotter M (2013) Farming the web of things. IEEE Intell Syst 28(6):12–19CrossRefGoogle Scholar
  20. Wald L (1999) Some terms of reference in data fusion. IEEE Trans Geosci Remote Sens 37(3):1190–1193CrossRefGoogle Scholar
  21. Wang F, Hu L, Zhou J, Zhao K (2015) A survey from the perspective of evolutionary process in the internet of things. Int J Distrib Sens Netw. doi:10.1155/2015/462752
  22. Wei X, Li H, Yang K, Zou L (2014) Topology-aware partial virtual cluster mapping algorithm on shared distributed infrastructures. IEEE Trans Parallel Distrib Syst 25(10):2721–2730CrossRefGoogle Scholar
  23. Yang K, Ou S, Guild K, Chen H-H (2009) Convergence of ethernet PON and IEEE 802.16 broadband access networks and its QoS-aware dynamic bandwidth allocation scheme. IEEE J Sel Area Commun 27(2):101–116. doi:10.1109/JSAC.2009.090202
  24. Yang G, Xie L, Mantysalo M, Zhou XL, Pang ZB, Xu LD, Kao-Walter S, Chen Q, Zheng LR (2014) A health-IoT platform based on the integration of intelligent packaging, unobtrusive bio-sensor, and intelligent medicine box. IEEE Trans Ind Inform 10(4):2180–2191 (WOS:000344995800020)Google Scholar
  25. Zhao F, Sun Z, Jin H (2015) Topic-centric and semantic-aware retrieval system for internet of things. Inf Fusion 23:33–42. http://www.sciencedirect.com/science/article/pii/S1566253514000062
  26. Zhou J, Hu L, Wang F, Zhao K (2013) An efficient multidimensional fusion algorithm for IoT data based on partitioning. Tsinghua Sci Technol 18(4). doi:10.1109/TST.2013.6574675

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Feng Wang
    • 1
  • Liang Hu
    • 1
  • Jin Zhou
    • 2
  • Jiejun Hu
    • 1
  • Kuo Zhao
    • 1
  1. 1.College of Computer Science and TechnologyJilin UniversityChangchunChina
  2. 2.College of Information Science and TechnologyBohai UniversityJinzhouChina

Personalised recommendations