An Architectural Model for Smart Cities using Collaborative Spatial Data Infrastructures

Aly C. S. Rabelo, Italo L. Oliveira, Jugurta Lisboa-Filho

2017

Abstract

Smart cities make intense use of information technologies to capture data in real time in order to automate urban management and social actions. However, the implementation of this concept is hindered by its complexity and limitations in cities. Using a model that contains the basic concepts of a smart city ensures such basic concepts will be approached during specification, besides facilitating communication among designers and allowing the evolution of a smart city to be followed. The International Cartographic Association (ICA) has developed a formal model for Spatial Data Infrastructure (SDI) using the Enterprise, Information, and Computation viewpoints of the Reference Model for Open Distributed Processing (RM-ODP) framework. Assuming that an SDI and volunteered geographic data (VGI) are key parts of a smart city, this study adapts ICA’s formal model for SDI with basic concepts that a smart city must have. The adapted model was applied in the specification of the Enterprise viewpoint of a system to reduce traffic congestion. The specification enabled exemplifying the importance of SDI and VGI in the context of a basic architecture for the implementation of applications aiming to turn small and medium-sized cities into smart.

References

  1. Béjar, R., Latre, M. Í., Nogueras-Iso, J., Muro-Medrano, P. R., and Zarazaga-Soria, F. J. (2012). An rm-odp enterprise view for spatial data infrastructures. Computer Standards & Interfaces, 34(2):263-272.
  2. Caragliu, A., Del Bo, C., and Nijkamp, P. (2011). Smart cities in europe. Journal of urban technology, 18(2):65-82.
  3. Cooper, A. K. et al. (2011). Extending the formal model of a spatial data infrastructure to include volunteered geographical information.
  4. Cooper, A. K. et al. (2013). A spatial data infrastructure model from the computational viewpoint. International Journal of Geographical Information Science, 27(6):1133-1151.
  5. Da Silva, W. M. et al. (2013). Smart cities software architectures: a survey. In Proceedings of the 28th Annual ACM Symposium on Applied Computing, pages 1722- 1727. ACM.
  6. DENATRAN (2010). Manual brasileiro de fiscalizac¸a˜o de traˆnsito - competeˆncia municipal, incluindo as concorrentes dos órga˜os e entidades estaduais de traˆnsito e rodoviários. In Manual de orientac¸a˜o Aprovado pelo CONTRAN na Resoluc¸a˜o No 371, de 10 de dezembro de 2010, volume 1, page 26.
  7. Fernández, M. J., Ílvarez, P., López, F., and Muro, P. (2006). Idezar: un ejemplo de implantación de una ide en la administración local. Actas de las IX Jornadas Sobre Tecnologías de la Informaci ón para la Modernización de las Administraciones Públicas (Tenimap 2006). Sevilla, Espan˜a.
  8. Giffinger, R. et al. (2007). Smart cities: Ranking of european medium-sized cities. vienna, austria: Centre of regional science (srf), vienna university of technology.
  9. Hjelmager, J. et al. (2008). An initial formal model for spatial data infrastructures. International Journal of Geographical Information Science, 22(11-12):1295- 1309.
  10. ISO/DIS 37120 (2013). Sustainable development and resilience of communities - indicators for city services and quality of life. INTERNATIONAL ORGANIZATION, 2013:08-27.
  11. Kyriazopoulou, C. (2015). Architectures and requirements for the development of smart cities: A literature study. In International Conference on Smart Cities and Green ICT Systems, pages 75-103. Springer.
  12. Linington, P. F., Milosevic, Z., Tanaka, A., and Vallecillo, A. (2011). Building enterprise systems with ODP: an introduction to open distributed processing. CRC Press.
  13. Oliveira, I. L. and Lisboa Filho, J. (2015). A spatial data infrastructure review - sorting the actors and policies from enterprise viewpoint.
  14. Organization, W. H. et al. (2016). World health statistics 2016: monitoring health for the sdgs, sustainable development goals.
  15. Percivall, G. et al. (2015). Ogc smart cities spatial information framework. OGC White Paper.
  16. Pérez-Martínez, P. A., Mart ínez-Ballest é, A., and Solanas, A. (2013). Privacy in smart cities-a case study of smart public parking. In PECCS, pages 55-59.
  17. Pérez Pérez, M. et al. (2013). Infraestructuras de datos espaciales como eje central del desarrollo de las smart cities. IV JORNADAS IB ÓRICAS DE INFRAESTRUTURAS DE DADOS ESPACIAIS. Toledo, Espanha.
  18. Seto, K. C. et al. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences, 109(40):16083-16088.
  19. Su, K., Li, J., and Fu, H. (2011). Smart city and the applications. In Electronics, Communications and Control (ICECC), 2011 International Conference on, pages 1028-1031. IEEE.
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Paper Citation


in Harvard Style

Rabelo A., Oliveira I. and Lisboa-Filho J. (2017). An Architectural Model for Smart Cities using Collaborative Spatial Data Infrastructures . In Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-241-7, pages 242-249. DOI: 10.5220/0006306102420249


in Bibtex Style

@conference{smartgreens17,
author={Aly C. S. Rabelo and Italo L. Oliveira and Jugurta Lisboa-Filho},
title={An Architectural Model for Smart Cities using Collaborative Spatial Data Infrastructures},
booktitle={Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2017},
pages={242-249},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006306102420249},
isbn={978-989-758-241-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - An Architectural Model for Smart Cities using Collaborative Spatial Data Infrastructures
SN - 978-989-758-241-7
AU - Rabelo A.
AU - Oliveira I.
AU - Lisboa-Filho J.
PY - 2017
SP - 242
EP - 249
DO - 10.5220/0006306102420249