Information

Scope

Ambient Intelligence (AmI) is intended to provide users with systems tightly integrated with their everyday environment and activities. The goal is minimizing the need of explicit actions by users, through the continuous and distributed orchestration of information and actuation devices. With the advances in the field, AmI is pursuing growingly ambitious goals in terms of the size and integration of its smart spaces, the number of served users, and the level of adaptation to them.

This special session will be focused on the challenges and potential solutions that appear when AmI moves to Large Premises (LP). In this context, new requirements consider big groups of people moving in premises that fall beyond the classical closed and controlled environments of most AmI systems. The ways of interaction, the expected services, and the behaviour of people acquire a new dimension and variability in those interconnected smart spaces. AmI systems need to adapt to the crowds using large numbers of multiple and heterogeneous AmI resources in distributed and frequently uncontrollable environments that cause unexpected dynamic changes in the system topology.


Topics

  • Psychology of crowds
  • Sociology of crowds
  • Crowd simulation
  • Crowd coordination
  • Environment specifications and models
  • Inclusive design
  • Sensor networks
  • Information fusion
  • Machine learning
  • Agent-based social simulation
  • Agent-based simulation techniques and methodologies
  • Ambient Intelligence (AmI)
  • AmI engineering driven by formal models
  • AmI toolkits and frameworks
  • AmI testing in large premises
  • Industrial case studies
  • Scalability in AmI for large premises

Committee

Organizing Committee

  • Alberto Fernandez, University Rey Juan Carlos
  • Jorge J. Gómez, Universidad Complutense de Madrid
  • Ramón Alcarria, Universidad Politécnica de Madrid
  • Álvaro Carrera, Universidad Politécnica de Madrid


Program Committee

  • Carlos A. Iglesias. Universidad Politécnica de Madrid (Spain)
  • Geylani Kardas Ege. University International Computer Institute (Turkey)
  • Gianluca Rizzo. HES SO Valais (Switzerland)
  • Holger Billhardt. Universidad Rey Juan Carlos (Spain)
  • Iván García-Magariño. University of Zaragoza (Spain)
  • Juan Pavón. Universidad Complutense de Madrid (Spain)
  • Juergen Dunkel. FH Hannover - University for Applied Sciences and Arts (Germany)
  • Marin Lujak. IMT Lille Douai (France)
  • Paulo Novais. University of Minho (Portugal)
  • Rubén Fuentes-Fernández. Universidad Complutense de Madrid (Spain)
  • Sascha Ossowski. University Rey Juan Carlos (Spain)
  • Tomás Robles. Universidad Politécnica de Madrid (Spain)

Contact

Alberto Fernández Gil
alberto.fernandez@urjc.es
Universidad Rey Juan Carlos
C/. Tulipán, s/n. 28933 Móstoles. Madrid. Spain