Skip to main content

Semantic IoT: The Key to Realizing IoT Value

  • Chapter
  • First Online:
Semantic IoT: Theory and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 941))

Abstract

The virtual representation and integration of the internet with the physical objects, devices or things have been growing exponentially in recent years. This has motivated the community to design and develop new Internet of Things (IoT) platforms to cater, capture, access, store, share, and communicate data for information retrieval and intelligent applications. However, the associated dynamism, resource-constrain, cost and the nature of the IoT warrants special design obligations for its effectiveness in the days ahead, hence pose a challenge to the community. The understanding of web data from machines according to the subject of terminology in different fields is a complex task. It opens up new challenges to researchers as such an effort mandates the provision of semantically structured, appropriate information sources in this information age. The advent of numerous smart devices, operators, and IoT service providers subject to time-consuming and complex operations, inadequate research and innovations give rise to design complexity. For efficient functioning and effective implementation of the domain requires the inclusion of semantics and the desired interoperability among these factors. This motivates the authors to review and emphasizes a few of the emerging trends of the semantic technology impacting the IoT. Particularly, the work focuses on different aspects as information modeling, ontology design, machine learning, network tools, security policy and processing of semantic data—and discuss the issues and challenges in the current scenario.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Van Kranenburg, R., Bassi, A.: IoT challenges. Commun. Mob. Comput. 1(9), 1–5 (2012)

    Google Scholar 

  2. Atzori, L., Iera, A., Morabito, G.: The internet of things: a survey. Comput. Net. 54(15), 2787–2805 (2010)

    Article  Google Scholar 

  3. Evans, D.: The internet of things: how the next evolution of the internet is changing everything. CISCO White Pap. 1, 1–11 (2011)

    Google Scholar 

  4. Berners-Lee, T., Hendler, J., Lassila, O.: The semantic web. SciAm 284(5), 28–37 (2001)

    Google Scholar 

  5. Berners-Lee, T.: Linked data. Int. J. Semant. Web. Inf. Syst. 4(2) (2006)

    Google Scholar 

  6. McIlraith, A., Son, T.C., Zeng, H.: Semantic web services. IEEE Intell. Syst. 16, 46–53 (2001)

    Article  Google Scholar 

  7. Greenough, J.: The US smart home market has been struggling-here’s how and why the market will take off. Business insider. Available online https://www.businessinsider.com/the-us-smart-home-marketreport-adoption-forecasts-top-products-and-the-cost-and-fragmentation-problems-that-could-hindergrowth-2015-9 (2016)

  8. Al-Osta, M., Ahmed, B., Abdelouahed, G.: A lightweight semantic web-based approach for data annotation on IoT gateways. Proc. Comp. Sci. 113, 186–193 (2017)

    Article  Google Scholar 

  9. Zhang, H., Li, Y.F., Tan, H.B.K.: Measuring design complexity of semantic web ontologies. J. Syst. Softw. 83(5), 803–814 (2010)

    Article  Google Scholar 

  10. Amarilli, F., Amigoni, F., Fugini, M.G., Zarri, G.P.: A semantic-rich approach to IoT using the generalized world entities paradigm. In: Managing the Web of Things. Morgan Kaufmann, pp. 105–147 (2017)

    Google Scholar 

  11. Gomes, P., et al.: A semantic-based discovery service for the internet of things. J. Internet Serv. Appl. 10(10), 2–14 (2019)

    Google Scholar 

  12. INFSO D.4 Networked Enterprise and RFID INFSO G.2 Micro and Nanosystems. In Co-operation with the Working Group RFID of the ETP EPOSS, Internet of Things in 2020, Roadmap for the Future, Version 1.1, 27 May 2008

    Google Scholar 

  13. Toma, I., Simperl, E., Hench, G.: A joint roadmap for semantic technologies and the internet of things. In: Proceedings of the Third STI Road Mapping Workshop, Crete, Greece (2009)

    Google Scholar 

  14. Vyas, D.A., Bhatt, D., Jha, D.: IoT: trends, challenges and future scope. Int. J. Comput. Commun. 7(1), 186–197 (2015)

    Google Scholar 

  15. Shi, F., Li, Q., Zhu, T., Ning, H.: A survey of data somatization in internet of things. Sensors 18(1), 2–20 (2018)

    Article  Google Scholar 

  16. Serrano, M., Barnaghi, P., Carrez, F., Cousin, P., Vermesan, O., Friess, P.: Internet of things IoT semantic interoperability: research challenges, best practices, recommendations and next steps. In: IERC: European Research Cluster on the Internet of Things, Tech. Rep (2015)

    Google Scholar 

  17. Gyrard, A., Serrano, M.: Connected smart cities: interoperability with SEG 3.0 for the internet of things. In: Proceedings of 30th IEEE International Conference on Advanced Information Networking and Applications Workshops, pp. 796–802 (2016)

    Google Scholar 

  18. Hahm, O., Baccelli, E., Petersen, H., Tsiftes, N.: Operating systems for low-end devices in the internet of things: a survey. IEEE Internet Things J. 3(5), 720–734 (2016)

    Article  Google Scholar 

  19. Bello, O., Zeadally, S., Badra, M.: Network Layer Inter-Operation of Device-to-Device communication technologies in Internet of Things (IoT). Ad Hoc Networks, pp. 1–11 (2016)

    Google Scholar 

  20. Noura, M., Atiquzzaman, M., Gaedke, M.: Interoperability in internet of things: taxonomies and open challenges. Mob. Netw. Appl. 24, 796809 (2019)

    Google Scholar 

  21. W3C: Semantic Integration and Interoperability Using RDF and OWL. www.w3.org/2001/sw/BestPractices/OEP/SemInt (2018)

  22. Jabbar, S., Ullah, F., Khalid, S., Khan, M., Han, K.: Semantic interoperability in heterogeneous IoT infrastructure for healthcare. Wirel. Commun. Mob. Comput. 9731806, 1–10 (2017)

    Article  Google Scholar 

  23. Serrano, M., Gyrard, A.: A review of tools for IoT semantics and data streaming analytics. Build. Blocks IoT Anal. 6, 139–163 (2015)

    Google Scholar 

  24. Swetina, J., Lu, G., Jacobs, P., Ennesser, F., Song, J.: Toward a standardized common M2M service layer platform: Introduction to oneM2M. IEEE Wirel. Commun. 21(3), 20–26 (2014)

    Article  Google Scholar 

  25. Mohanty, M.N., Palo, H.K.: Segment based emotion recognition using combined reduced features. Int. J. Speech Tech. 22(4), 865–884 (2019)

    Article  Google Scholar 

  26. Palo, H.K., Mohanty, M.N., Chandra, M.: Efficient feature combination techniques for emotional speech classification. Int. J .Speech Tech. 19(1), 135–150 (2016)

    Article  Google Scholar 

  27. Palo, H.K., Sagar, S.: Comparison of neural network models for speech emotion recognition. In: 2nd IEEE International Conference on Data Science and Business Analytics (ICDSBA), pp. 127–131 (2018)

    Google Scholar 

  28. Khan, A.M., Lee, Y.K., Lee, S.Y., Kim, T.S.: A triaxial accelerometer-based physical-activity recognition via augmented-signal features and a hierarchical recognizer. IEEE Trans. Inf. Technol. B 14(5), 1166–1172 (2010)

    Article  Google Scholar 

  29. Altun, K., Barshan, B.: Human activity recognition using inertial/magnetic sensor units. In: International Workshop on Human Behavior Understanding. Springer, Berlin, Heidelberg, pp. 38–51 (2010)

    Google Scholar 

  30. Lane, N.D., Bhattacharya, S., Georgiev, P., Forlivesi, C., Kawsar, F.: An early resource characterization of deep learning on wearables, smartphones and internet of things devices. In: International Workshop on Internet of Things towards Applications. ACM, pp. 7–12 (2015)

    Google Scholar 

  31. Chen, Y., Zhou, J., Guo, M.: A context-aware search system for internet of things based on hierarchical context model. Telecommun. Syst. 62(1), 77–91 (2016)

    Article  Google Scholar 

  32. Bhide, V.H., Wagh, S.: I-learning IoT: an intelligent self learning system for home automation using IoT. Int. Conf. Commun. Sig. Process. 1763–1767 (2015)

    Google Scholar 

  33. https://www.accenture.com/_acnmedia/pdf-77/accenture-pulse-survey.pdf (2018)

  34. Ruta, M., Scioscia, F., Loseto, G., Pinto, A., Di Sciascio, E.: Machine Learning in the Internet of Things: a Semantic-enhanced Approach. Semantic Web, IOS Press, pp. 1–22 (2018)

    Google Scholar 

  35. Sezer, O.B., Dogdu, E., Ozbayoglu, M., Onal, A.: An extended IOT framework with semantics, big data, and analytics. In: IEEE International Conference on Big Data (Big Data), pp. 849–1856 (2016)

    Google Scholar 

  36. Koru, A.G., Tian, J.: An empirical comparison and characterization of high defect and high complexity modules. J. Syst. Softw. 67(3), 153–163 (2003)

    Article  Google Scholar 

  37. Weyuker, E.J.: Evaluating software complexity measures. IEEE Trans. Softw. Eng. 14(9), 1357–1365 (1988)

    Article  MathSciNet  Google Scholar 

  38. Yao, H., Orme, A.M., Etzkorn, L.: Cohesion metrics for ontology design and application. J. Comput. Sci. 1(1), 107–113 (2005)

    Article  Google Scholar 

  39. Kang, D., Xu, B., Lu, J., Chu, W.C.: A complexity measure for ontology based on UML. In: Proceedings of 10th IEEE Int Workshop on Future Trends of Distributed Computing Systems (FTDCS’04), IEEE CS, Washington, DC, USA, pp. 222–228 (2004)

    Google Scholar 

  40. Gangemi, A., Catenacci, C., Ciaramita, M., Lehmann, J.: Modelling ontology evaluation and validation. In: Proceedings of 3rd European Semantic Web Conference (ESWC’06). Budva, Montenegro, pp. 140–154 (2006)

    Google Scholar 

  41. Wang, T.D., Parsia, B., Hendler, J.A.: A survey of the web ontology landscape. In: International Semantic Web Conference on Lecture Notes Computer Science, vol. 4273. Springer, pp. 682–694 (2006)

    Google Scholar 

  42. Vrandečić, D., Sure, Y.: How to design better ontology metrics. In: ESWC’07: Proceedings of 4th European Conference on the Semantic Web. Springer-Verlag, Innsbruck, Austria, pp. 311–325 (2007)

    Google Scholar 

  43. Das, S.K., Palo, H.K.: Internet of Things (IoT) Application in Green Computing: an Overview. Advances in Greener Energy Technologies. Springer, Singapore, pp. 85–102 (2020)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hemanta Kumar Palo .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Palo, H.K. (2021). Semantic IoT: The Key to Realizing IoT Value. In: Pandey, R., Paprzycki, M., Srivastava, N., Bhalla, S., Wasielewska-Michniewska, K. (eds) Semantic IoT: Theory and Applications. Studies in Computational Intelligence, vol 941. Springer, Cham. https://doi.org/10.1007/978-3-030-64619-6_4

Download citation

Publish with us

Policies and ethics