Smart cities simulation environment for intelligent algorithms evaluation

• CHAMOSO, Pablo ^[1] ; DE LA PRIETA, Fernando ^[2]
  1. [1] Catholic University of Daegu

     Catholic University of Daegu

     Corea del Sur

     
  2. [2] National University of Sunchon
• Localización: ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, ISSN-e 2255-2863, Vol. 4, Nº. 3, 2015, págs. 87-96
• Idioma: inglés
• DOI: 10.14201/ADCAIJ2015438796
• Enlaces
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• Resumen

  • This article presents an adaptive platform that can simulate the centralized control of different smart city areas. For example, public lighting and intelligent management, public zones of buildings, energy distribution, etc. It can operate the hardware infrastructure and perform optimization both in energy consumption and economic control from a modular architecture which is fully adaptable to most cities. Machine-to-machine (M2M) permits connecting all the sensors of the city so that they provide the platform with a perfect perspective of the global city status. To carry out this optimization, the platform offers the developers a software that operates on the hardware infrastructure and merges various techniques of artificial intelligence (AI) and statistics, such as artificial neural networks (ANN), multi-agent systems (MAS) or a Service Oriented Approach (SOA), forming an Internet of Services (IoS). Different case studies were tested by using the presented platform, and further development is still underway with additional case studies.

• Referencias bibliográficas
  • Calvillo, C. F., Sánchez-Miralles, A., & Villar, J. (2016). Energy management and planning in smart cities. Re-newable and Sustainable...
  • Chamoso, P., De la Prieta, F., De Paz, F., & Corchado, J. M. (2015). Swarm Agent-Based Architecture Suitable for Internet of Things and...
  • Chamoso, P., De la Prieta, F., Bajo, J., & Corchado, J. M. (2016). Conflict Resolution with Agents in Smart Ci-ties. Interdisciplinary...
  • Chourabi, H., Nam, T., Walker, S., Gil-Garcia, J. R., Mellouli, S., Nahon, K., Pardo, T. A., and Scholl, H. J. (2012). Understanding Smart...
  • Gómez-Romero, J., Serrano, M. A., Patricio, M. A., García, J., & Molina, J. M. (2012). Context-based scene recognition from visual data...
  • Naphade, M., Banavar, G., Harrison, C., Paraszczak, J., & Morris, R. (2011). Smarter cities and their innovation challenges. Computer,...
  • Washburn, D., Sindhu, U., Balaouras, S., Dines, R. a, Hayes, N., and Nelson, L. E. (2009). Helping CIOs Un-derstand "Smart City" Initiatives....