Abstract
Contemporary smart cities involve a very high number of software applications and hardware devices that connect to the physical and social space of cities and form complex global ecosystems in different knowledge and activity domains (transportation, logistics, healthcare, local communities, industry, governance, social care and many more). In this context, smart cities can be considered multi-layered complex systems, systems of systems, that provide ubiquitous access to services, applications, platforms, and infrastructures. Although the inherent heterogeneity of Internet-of-Things (IoT) devices and their platforms, is one of the challenges smart city ecosystems face, several implementations promote digital transformation methodologies that attempt to bridge the different domains. Multiple IoT and software platforms, ranging from open source to proprietary solutions, implement different architectures and communication protocols for exchanging data streams. The diversity of these platforms though disrupts the creation of smart city ecosystems and prohibits the establishment of holistic and universal access models.
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References
Komninos, N., Kakderi, C., Mora, L., Panori, A., Sefertzi, E.: Towards high impact smart cities: a universal architecture based on connected intelligence spaces. J. Knowl. Econ. 4, 1–29 (2021). https://doi.org/10.1007/s13132-021-00767-0
Komninos, N.: Architectures of intelligence in smart cities: pathways to problem-solving and innovation. ArchiDoct. 6(1), 11 (2018)
IoT Analytics: State of IoT 2021. https://iot-analytics.com/number-connected-iot-devices. Accessed 29 Jan 2022
IIoT World: The Smart City Ecosystem Framework – A Model for Planning Smart Cities. https://www.iiot-world.com/smart-cities-buildings-infrastructure/smart-cities/the-smart-city-ecosystem-framework-a-model-for-planning-smart-cities. Accessed 29 Jan 2022
Danielsen, F., Flak, L.S., Ronzhyn, A.: Cloud computing in e-government: benefits and challenges. In: ICDS 2019: The Thirteenth International Conference on Digital Society and eGovernments, Athens, Greece (2019)
Gartner Inc.: Hype Cycle for Digital Government Technology, 2021, Alia Mendonsa, 21 July 2021, Whitepaper (2021)
Mineraud, J., Mazhelis, O., Su, X., Tarkoma, S.: A gap analysis of Internet-of-Things platforms. Comput. Commun. 89–90, 5–16 (2016). https://doi.org/10.1016/j.comcom.2016.03.015
What is IoT Architecture: MongoDB. https://www.mongodb.com/cloud-explained/iot-architecture. Accessed 29 Jan 2022
Tsampoulatidis, I., Nikolopoulos, S., Kompatsiaris, I., Komninos, N.: Geographic citizen science in citizen-government communication and collaboration: lessons learned from the Improve My City application. In: Geographic Citizen Science Design: No one Left Behind, pp. 186–205. UCL Press (2021)
Chalikias, A.P., et al.: Evidence-driven policy-making using heterogeneous data sources—the case of a controlled parking system in Thessaloniki. Data Policy 2(2020), e15 (2021)
Pereira, J., Batista, T., Cavalcante, E., Souza, A., Lopes, F., Cacho, N.: A platform for integrating heterogeneous data and developing smart city applications. Futur. Gener. Comput. Syst. 128(March), 552–566 (2022). https://doi.org/10.1016/j.future.2021.10.030
Trilles, S., Calia, A., Belmonte, Ó., Torres-Sospedra, J., Montoliu, R., Huerta, J.: Deployment of an open sensorized platform in a smart city context. Futur. Gener. Comput. Syst. 76(November), 221–233 (2017). https://doi.org/10.1016/j.future.2016.11.005
Massana, J., Pous, C., Burgas, L., Melendez, J., Colomer, J.: Identifying services for short-term load forecasting using data driven models in a smart city platform. Sustain. Cities Soc. 28(January), 108–117 (2017). https://doi.org/10.1016/j.scs.2016.09.001
Pardo-García, N., Simoes, S.G., Dias, L., Sandgren, A., Suna, D., Krook-Riekkola, A.: Sustainable and resource efficient cities platform – SureCity holistic simulation and optimization for smart cities. J. Clean. Prod. 215(April), 701–711 (2019). https://doi.org/10.1016/j.jclepro.2019.01.070
Badii, C., Bellini, P., Difino, A., Nesi, P., Pantaleo, G., Paolucci, M.: Microservices suite for smart city applications. Sensors (Switzerland) 19(21), 4798 (2019). https://doi.org/10.3390/s19214798
Yu, J., Wen, Y., Jin, J., Zhang, Y.: Towards a service-dominant platform for public value co-creation in a smart city: evidence from two metropolitan cities in China. Technol. Forecast. Soc. Chang. 142(May), 168–182 (2019). https://doi.org/10.1016/j.techfore.2018.11.017
Chamoso, P., González-Briones, A., de La Prieta, F., Venyagamoorthy, G.K., Corchado, J.M.: Smart city as a distributed platform: toward a system for citizen-oriented management. Comput. Commun. 152 (February), 323–32 (2020). https://doi.org/10.1016/j.comcom.2020.01.059
Miguel, J.C., Casado, M.A.: GAFAnomy (Google, Amazon, Facebook and Apple): The Big Four and the b-Ecosystem (2016)
Kubler, S., et al.: IoT platforms initiative. In: Vermesan, O., Friess, P., (Eds.), “Internet of Things Connecting the Physical, Digital and Virtual Worlds: Digitising the Industry, pp. 265–292 (2016)
Chaturvedi, K., Kolbe, T.: Towards establishing cross-platform interoperability for sensors in smart cities. Sensors. 19(3), 562 (2019). https://doi.org/10.3390/s19030562
Broring, A., et al.: Enabling IoT ecosystems through platform interoperability. IEEE Softw. 34(1), 54–61 (2017). https://doi.org/10.1109/MS.2017.2
Javed, A., et al.: BIoTope: building an IoT open innovation ecosystem for smart cities. IEEE Access. 8, 224318–224342 (2020). https://doi.org/10.1109/access.2020.3041326
Kazmi, A., Jan, Z., Zappa, A., Serrano, M.: Overcoming the heterogeneity in the internet of things for smart cities. In: Podnar Žarko, I., Broering, A., Soursos, S., Serrano, M. (eds.) Interoperability and Open-Source Solutions for the Internet of Things. LNCS, vol. 10218, pp. 20–35. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-56877-5_2
Bengt, A., et al.: Internet of things for smart cities: interoperability and open data. IEEE Internet Comput. 20(6), 52–56 (2016). https://doi.org/10.1109/mic.2016.124
Robert, J., et al.: Open IoT ecosystem for enhanced interoperability in smart cities—example of Métropole de Lyon. Sensors. 17(12), 2849 (2017). https://doi.org/10.3390/s17122849
Javed, A., Malhi, A., Kinnunen, T., Framling, K.: Scalable IoT platform for heterogeneous devices in smart environments. IEEE Access 8, 211973–211985 (2020). https://doi.org/10.1109/access.2020.3039368
Liu, X., Heller, A., Nielsen, P.S.: CITIESData: a smart city data management framework. Knowl. Inf. Syst. 53(3), 699–722 (2017). https://doi.org/10.1007/s10115-017-1051-3
Bischof, S., Karapantelakis, A., Nechifor, C.S., Sheth, A.P., Mileo, A., Barnaghi, P.: Semantic modelling of smart city data (2014)
Gupta, A., Panagiotopoulos, P., Bowen, F.: An orchestration approach to smart city data ecosystems. Technol. Forecast. Soc. Chang. 153, 119929 (2020)
ΙΒΜ: Thessalonki, Greece. Smarter Cities Challenge report. IBM Corporate Citizenship & Corporate Affairs (2017)
Gaia-X: https://www.gaia-x.eu. Accessed 29 Jan 2022
Gaia-X: Gaia-X architecture document. Gaia-X European Association for Data and Cloud AISBL (2021)
Autolitano, S., Pawlowska, A.: Europe’s quest for digital sovereignty: GAIA-X as a case study. IAI Papers. 21, 14 (2021)
Wilkinson, M.D., et al.: The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3(1), 1–9 (2016)
van Reisen, M., Stokmans, M., Basajja, M., Ong’ayo, A.O., Kirkpatrick, C., Mons, B.: Towards the tipping point for FAIR implementation. Data Intell. 2(1–2), 264–275 (2020)
Komninos, N.: Smart Cities and Connected Intelligence: Platforms, Ecosystems and Network Effect Regions and Cities Series. Routledge, Milton Park (2021)
Tsampoulatidis, I., Bechtsis, D., Kompatsiaris, I.: Moving from e-Gov to we-Gov and beyond: a blockchain framework for the digital transformation of cities. In: Smart Cities in the Post-algorithmic Era: Integrating Technologies, Platforms and Governance, pp. 176–200. Edward Elgar (2019)
Komninos, N., Panori, A., Kakderi, C.: Smart cities beyond algorithmic logic: digital platforms, user engagement and data science. In: Smart Cities in the Post-algorithmic Era: Integrating Technologies, Platforms and Governance, pp. 1–15. Edward Elgar (2019)
Acknowledgments
The research work of two of the authors (D. Bechtsis and E. Syrmos) was supported by the European Regional Development Fund (ERDF) 2014–2020, Central Macedonia Operational Programme, Project ‘iWet: Intelligent IoT System for Quantitative and Qualitative Measurements for water distribution networks’ MIS 5136429.
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Tsampoulatidis, I., Komninos, N., Syrmos, E., Bechtsis, D. (2022). Universality and Interoperability Across Smart City Ecosystems. In: Streitz, N.A., Konomi, S. (eds) Distributed, Ambient and Pervasive Interactions. Smart Environments, Ecosystems, and Cities. HCII 2022. Lecture Notes in Computer Science, vol 13325. Springer, Cham. https://doi.org/10.1007/978-3-031-05463-1_16
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