Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

A Novel Approach for Calculating Real-Time Composite Indicators Relying on Internet of Things and Industrial Data Spaces

  • Conference paper
  • First Online:
Intelligent Distributed Computing XIV (IDC 2021)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1026))

Included in the following conference series:

  • 672 Accesses

Abstract

This paper aims at devising an IoT-based system to collaboratively calculate quantitative composite indicators among Industrial actors. Requirements have been considered to build a reliable, trusted, anonymised environment within which involved stakeholders can safely share information on the indicators while keeping sovereignty over their data. Technologies such as enhanced Context Brokers, the usage of Industrial Data Spaces agents and the introduction of distributed publish-subscribe data exchange schemes lay the foundations of the proposed solution. This work entails the design of the system altogether with a proposal of technologies for its deployment. Drawing from previous public-funded projects’ results and highly relying on open-source technologies, the authors have come up with a solution that aims to be proven in real environments in the near future.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
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

Similar content being viewed by others

References

  1. Erna Ruijer, Designing and implementing data collaboratives: A governance perspective, Government Information Quarterly, 2021, 101612, ISSN 0740-624X

    Google Scholar 

  2. Mazziotta, M., Pareto, A.: Synthesis of indicators: the composite indicators approach (2017). https://doi.org/10.1007/978-3-319-60595-1

  3. Smidova, Z.: Building the evidence for OECD integrity and anti-corruption agenda: the current situation and avenues for future analysis. OECD Economics Department Working Papers, No. 1614, OECD Publishing, Paris (2020). https://doi.org/10.1787/80ebe6e6-en

  4. https://europa.eu/youreurope/business/product-requirements/standards/standards-in-europe/index_en.htm

  5. https://internationaldataspaces.org/why/data-sovereignty/

  6. https://techjury.net/blog/how-many-iot-devices-are-there/#gref

  7. https://inter-iot.eu/

  8. https://european-iot-pilots.eu/project/create-iot/

  9. https://www.marketwatch.com/press-release/iot-integration-market-report-2021-to-2030-globally-exploring-sales-volume-revenue-and-price-by-types-2021-07-09?siteid=bigcharts&dist=bigcharts&tesla=y

  10. Saisana, M., Tarantola, S.: State-of-the-art report on current methodologies and practices for composite indicator development, EUR 20408 EN. European Commission-JRC, Italy (2002)

    Google Scholar 

  11. Hudrliková, L.: Composite indicators as a useful tool for international comparison: the Europe 2020 example. Prague Econ. Pap. 22, 459–473 (2013). https://doi.org/10.18267/j.pep.462

  12. https://pixel-ports.eu/

  13. http://www.citykeys-project.eu/

  14. Otto, B., Lohmann, S., Steinbuß, S., Teuscher, A.: IDS Reference Architecture Model Industrial Data Space Version 2.0

    Google Scholar 

  15. https://dataports-project.eu/

  16. https://www.gaia-x.eu/

  17. https://i4trust.org/

  18. Lacalle, I., Belsa, A., Vaño, R., Palau, C.E.: Framework and methodology for establishing port-city policies based on real-time composite indicators and IoT: a practical use-case. Sensors 20(15), 4131 (2020). https://doi.org/10.3390/s20154131

    Article  Google Scholar 

  19. https://smartdatamodels.org/

  20. Sarabia-Jácome, D., Palau, C.E., Esteve, M., Boronat, F.: Seaport data space for improving logistic maritime operations. IEEE Access 8, 4372–4382 (2019)

    Article  Google Scholar 

  21. https://github.com/FIWARE/catalogue/tree/master/data-spaces

  22. https://github.com/FIWARE/catalogue

  23. https://pypi.org/project/pyngsi/

  24. https://github.com/Engineering-Research-and-Development/fiware-true-connector

  25. Alonso, Á., Pozo, A., Cantera, J.M., De la Vega, F., Hierro, J.J.: Industrial data space architecture implementation using FIWARE. Sensors 18(7), 2226 (2018). https://doi.org/10.3390/s18072226

    Article  Google Scholar 

  26. Munoz-Arcentales, A., López-Pernas, S., Pozo, A., Alonso, Á., Salvachúa, J., Huecas, G.: Data usage and access control in industrial data spaces: implementation using FIWARE. Sustainability 12(9), 3885 (2020). https://doi.org/10.3390/su12093885

    Article  Google Scholar 

  27. https://github.com/International-Data-Spaces-Association/DataspaceConnector

  28. https://industrial-data-space.github.io/trusted-connector-documentation/

Download references

Acknowledge of funding

This research was funded by the European Commission via the H2020-project DataPorts—grant number 871493—and via the H2020-project PIXEL—grant number 769355.

Author information

Authors and Affiliations

  1. Communications Department, Universitat Politècnica de València, València, Spain

    Andreu Belsa, Rafael Vaño, Ignacio Lacalle, Matilde Julián, Fernando Boronat & Carlos E. Palau

Authors
  1. Andreu Belsa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rafael Vaño
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ignacio Lacalle
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Matilde Julián
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Fernando Boronat
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Carlos E. Palau
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Andreu Belsa .

Editor information

Editors and Affiliations

  1. Computer Systems Engineering Department, Universidad Politécnica de Madrid, Madrid, Spain

    David Camacho

  2. DIIES Department, University of Reggio Calabria, Reggio Calabria, Italy

    Domenico Rosaci

  3. Department of Psychology, University of Milan Bicocca, Milan, Italy

    Giuseppe M. L. Sarné

  4. DICEAM Department, University of Reggio Calabria, Reggio Calabria, Italy

    Mario Versaci

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Belsa, A., Vaño, R., Lacalle, I., Julián, M., Boronat, F., Palau, C.E. (2022). A Novel Approach for Calculating Real-Time Composite Indicators Relying on Internet of Things and Industrial Data Spaces. In: Camacho, D., Rosaci, D., Sarné, G.M.L., Versaci, M. (eds) Intelligent Distributed Computing XIV. IDC 2021. Studies in Computational Intelligence, vol 1026. Springer, Cham. https://doi.org/10.1007/978-3-030-96627-0_5

Download citation

Publish with us

Policies and ethics

Search

Navigation