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SMART-FI: Exploiting Open IoT Data from Smart Cities in the Future Internet Society

  • Stefan Nastic
  • Javier CuboEmail author
  • Malena Donato
  • Schahram Dustdar
  • Örjan Guthu. Mats Jonsson
  • Ömer Özdemir
  • Ernesto Pimentel
  • M. Serdar Yümlü
Chapter
Part of the Internet of Things book series (ITTCC)

Abstract

Smart Cities of the future have a potential to serve as a holistic platform for generating values from the abundance of currently untapped human, societal and ICT capital. Currently, Smart Cities are ever-stronger facing numerous challenges and a stringent need to optimize their urban processes, infrastructure and facilities, such as urban transportation and energy management. Unfortunately, at the moment, small portion of urban data is being exploited for gaining better insights and optimizing Smart City processes. In this chapter, we introduce a novel Smart City platform being developed in the context of SMART-FI project. The SMART-FI platform aims to facilitate analyzing, deploying, managing and interoperating Smart City data analytics services. Firstly, SMART-FI strives to enable collecting the data from a variety of sources, such as sensors and public data sources. Secondly, the platform provides mechanisms for homogenizing the data coming from various networks and protocols. Finally, it provides facilities to develop, deploy and orchestrate novel, added-value Smart City data analytic services. To demonstrate the practical feasibility of the proposed solutions and showcase their benefits for the variety of involved stakeholders, SMART-FI will be piloted in three cities: Malaga (Spain), Karlshamn (Sweden), and Malatya (Turkey).

Notes

Acknowledgements

This work is sponsored by Joint Programming Initiative Urban Europe, ERA-NET, under project No. 5631209. The authors alone are responsible for the content.

References

  1. 1.
    Abid, T., M.R. Laouar, H. Zarzour, and M.T. Khadir. 2016. Smart cities based on web semantic technologies. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, UbiComp ’16, 1303–1308. New York, NY, USA, ACM.Google Scholar
  2. 2.
    AENOR. 2015. UNE 178301:2015. http://bit.ly/2g6LoeN.
  3. 3.
    Agrawal, Divyakant, Sudipto Das, and Amr El Abbadi. 2011. Big data and cloud computing: Current state and future opportunities. In Proceedings of the 14th International Conference on Extending Database Technology, EDBT/ICDT ’11, 530–533, New York, NY, USA, ACM.Google Scholar
  4. 4.
    Andrikopoulos, V., S. Benbernou, and M.P. Papazoglou. 2012. On the evolution of services. IEEE Transactions on Software Engineering, 38(undefined): 609–628.Google Scholar
  5. 5.
    Andrikopoulos, V. and P. Plebani. 2011. Retrieving compatible web services. 2011 IEEE International Conference on Web Services (ICWS 2011), 00(undefined): 179–186.Google Scholar
  6. 6.
    Autili Marco, Paola Inverardi, Alfredo Navarra, and Massimo Tivoli. 2007. Synthesis: A tool for automatically assembling correct and distributed component-based systems. In Proceedings of the 29th International Conference on Software Engineering, ICSE ’07, 784–787. Washington, DC, USA, IEEE Computer Society.Google Scholar
  7. 7.
    Bauer, Florian, and Martin Kaltenbock. 2011. Linked open data: The essentials. Edition mono/monochrom.Google Scholar
  8. 8.
    Bellini, P., M. Benigni, R. Billero, P. Nesi, and N. Rauch. 2014. Km4city ontology building vs data harvesting and cleaning for smart-city services. Journal of Visual Languages and Computing 25(6): 827–839.Google Scholar
  9. 9.
    Biem, Alain, Eric Bouillet, Hanhua Feng, Anand Ranganathan, Anton Riabov, Olivier Verscheure, Haris Koutsopoulos, and Carlos Moran. 2010. IBM infosphere streams for scalable, real-time, intelligent transportation services. In Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data, SIGMOD ’10, 1093–1104, New York, NY, USA, ACM.Google Scholar
  10. 10.
    Bischof, Stefan, Athanasios, Karapantelakis, and Cosmin-Septimiu, Nechifor, Amit P. Sheth, Alessandar Mileo, and Payam Barnaghi. 2014. Semantic modelling of smart city data. https://www.w3.org/2014/02/wot/papers/karapantelakis.pdf.
  11. 11.
    Bizer, Christian, Tom Heath, and Tim Berners-Lee. 2009. Linked data-the story so far. Semantic Services, Interoperability and Web Applications: Emerging Concepts.Google Scholar
  12. 12.
    Bowerman, B., J. Braverman, J. Taylor, H. Todosow, and U. Von Wimmersperg. 2000. The vision of a smart city. In 2nd International Life Extension Technology Workshop, Paris 28.Google Scholar
  13. 13.
    Brogi, Antonio, Javier Cmara, Carlos Canal, Javier Cubo, and Ernesto Pimentel. 2007. Dynamic contextual adaptation. Electronic Notes in Theoretical Computer Science 175(2): 81–95.Google Scholar
  14. 14.
    Brogi, Antonio and Razvan Popescu. 2006. Automated generation of bpel adapters. In Proceedings of the 4th International Conference on Service-Oriented Computing, ICSOC’06, 27–39. Springer, Berlin, Heidelberg.Google Scholar
  15. 15.
    Cámara, Javier, José Antonio Martín, Gwen Salaün, Javier Cubo, Meriem Ouederni, Carlos Canal, and Ernesto Pimentel. 2009. Itaca: an integrated toolbox for the automatic composition and adaptation of web services. In 2009 31st. International Conference on Software Engineering. ICSE2009. May 16–24. Vancouver, Canada. Proceedings, 627–630. IEEE Computer Society.Google Scholar
  16. 16.
    Canal, Carlos, Pascal Poizat, and Gwen Salaün. 2008. Model-based adaptation of behavioral mismatching components. IEEE Transactions on Software Engineering 34(4): 546–563.Google Scholar
  17. 17.
    Consoli, S., M. Mongiovic, A.G. Nuzzolese, S. Peroni, V. Presutti, R. Diego Reforgiato, and D. Spampinato. 2015. A smart city data model based on semantics best practice and principles. In Proceedings of the 24th International Conference on World Wide Web, WWW ’15 Companion, 1395–1400. New York, NY, USA, ACM.Google Scholar
  18. 18.
    Cubo, Javier, and Ernesto Pimentel. 2011. DAMASCo: A Framework for the Automatic Composition of Component-Based and Service-Oriented Architectures, 388–404. Springer, Berlin, Heidelberg.Google Scholar
  19. 19.
    Cuzzocrea, Alfredo, Il-Yeol Song, and Karen C. Davis. 2011. Analytics over large-scale multidimensional data: The big data revolution! In Proceedings of the ACM 14th International Workshop on Data Warehousing and OLAP, DOLAP ’11, 101–104. New York, NY, USA, ACM.Google Scholar
  20. 20.
    Demirkan, Haluk, and Dursun Delen. 2013. Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud. Decision Support Systems 55(1): 412–421.Google Scholar
  21. 21.
    European Commission. 2016. Making Big Data work for Europe. http://ec.europa.eu/digital-agenda/en/big-data.
  22. 22.
    Hashem, Ibrahim Abaker Targio, Ibrar Yaqoob, Nor Badrul Anuar, Salimah Mokhtar, Abdullah Gani, and Samee Ullah Khan. 2015. The rise of big data on cloud computing. Review and open research issues. Information Systems 47: 98–115.Google Scholar
  23. 23.
    Hollands, Robert, G. 2008. Will the real smart city please stand up? intelligent, progressive or entrepreneurial? City 12 (3): 303–320.Google Scholar
  24. 24.
    Lambda Architecture Net. 2016. Lambda Architecture. http://lambda-architecture.net/.
  25. 25.
    Manin, B. 1997. The Principles of Representative Government. Cambridge University Press.Google Scholar
  26. 26.
    Martin, J.A., F. Martinelli, and E. Pimentel. 2012. Synthesis of secure adaptors. The Journal of Logic and Algebraic Programming, 81(2):99–126. Formal Languages and Analysis of Contract-Oriented Software (FLACOS’10).Google Scholar
  27. 27.
    Marz, Nathan, and James Warren. 2015. Big Data: Principles and Best Practices of Scalable Realtime Data Systems, 1st ed. Greenwich, CT, USA: Manning Publications Co.Google Scholar
  28. 28.
    Motahari Nezhad, Hamid Reza, Boualem Benatallah, Axel Martens, Francisco Curbera, and Fabio Casati. 2007. Semi-automated adaptation of service interactions. In Proceedings of the 16th International Conference on World Wide Web, WWW ’07, 993–1002. New York, NY, USA, ACM.Google Scholar
  29. 29.
    Motahari Nezhad, Hamid Reza, Guang Yuan Xu, and Boualem Benatallah. 2010. Protocol-aware matching of web service interfaces for adapter development. In Proceedings of the 19th International Conference on World Wide Web, WWW ’10, 731–740. New York, NY, USA, ACM.Google Scholar
  30. 30.
    Papazoglou, Mike P. 2008. The challenges of service evolution. In Proceedings of the 20th International Conference on Advanced Information Systems Engineering, CAiSE ’08, 1–15. Springer, Berlin, Heidelberg.Google Scholar
  31. 31.
    Schaffers, Hans, Annika Sällström, Marc Pallot, José M. Hernández-Muñoz, Roberto Santoro, and Brigitte Trousse. 2011. Integrating living labs with future internet experimental platforms for co-creating services within smart cities. In Concurrent Enterprising (ICE), 2011 17th International Conference on, 1–11. IEEE.Google Scholar
  32. 32.
    Talia, Domenico. 2013. Clouds for scalable big data analytics. Computer 46(5): 98–101.Google Scholar
  33. 33.
    Toshniwal, Ankit, Siddarth Taneja, Amit Shukla, Karthik Ramasamy, Jignesh M. Patel, Sanjeev Kulkarni, Jason Jackson, Krishna Gade, Maosong Fu, Jake Donham, Nikunj Bhagat, Sailesh Mittal, and Dmitriy Ryaboy. 2014. Storm@twitter. In Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, SIGMOD ’14, 147–156. New York, NY, USA, ACM.Google Scholar
  34. 34.
    W3C Incubator Group Report. 2011. Semantic sensor network XG final report. http://www.w3.org/2005/Incubator/ssn/XGR-ssn.
  35. 35.
    Wetzstein, Branimir, Dimka Karastoyanova, Oliver Kopp, Frank Leymann, and Daniel Zwink. 2010. Cross-organizational process monitoring based on service choreographies. In Proceedings of the 2010 ACM Symposium on Applied Computing, SAC ’10, 2485–2490. New York, NY, USA, ACM.Google Scholar
  36. 36.
    Zulkernine, F. P. Martin, Y. Zou, M. Bauer, F. Gwadry-Sridhar, and A. Aboulnaga. 2013. Towards cloud-based analytics-as-a-service (claaas) for big data analytics in the cloud. In 2013 IEEE International Congress on Big Data, 62–69.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Stefan Nastic
    • 1
  • Javier Cubo
    • 2
    Email author
  • Malena Donato
    • 3
  • Schahram Dustdar
    • 1
  • Örjan Guthu. Mats Jonsson
    • 4
  • Ömer Özdemir
    • 3
  • Ernesto Pimentel
    • 2
  • M. Serdar Yümlü
    • 5
  1. 1.Distributed Systems GroupTu WienAustria
  2. 2.Dpto. Lenguajes Y Ciencias de la ComputaciónUniversidad de MálagaMálagaSpain
  3. 3.Atos Reserach and Innovation Unit in Atos Spain GroupMadridSpain
  4. 4.NetPort Science ParkKarlshamnSweden
  5. 5.SAMPAS Information & Communication SystemsIstanbulTurkey

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