Objective
The dynamic capture of situational awareness concerning crowds in specific mass gathering venues and its intelligent enablement into emergency management information systems, using smart communication devices and spaces is critical for achieving rapid, timely guidance and safe evacuation of people out of dangerous areas. Humans could be overwhelmed by fast changes of potentially dangerous incidents occurring at confined environments with mass-gathering. They could fail to make objective decisions to find their way to safety. This condition may lead to mass panic and make emergency management more challenging. In eVACUATE, the intelligent fusion of sensors, geospatial and contextual information, with advanced multi-scale crowd behaviour detection and recognition will be developed. The structured fusion of sensing information with dynamic estimated uncertainties on behaviour predictions will advance eVACUATE crowd dynamic models; and virtual reality simulations of crowds in confined environments. A service oriented Decision-Support System shall be developed to dynamically distribute on-demand evacuation information to emergency management actors as the crisis unfolds. Decision-makers at the command posts, first responders, front-line stewards and volunteers receive real-time situation aware information of updated evacuation strategies using robust and resilient eVACUATE information and communication infrastructure. Smart spaces of electronic, audio and other mobile devices shall be connected to the integrated system to provide safer evacuation routings for people. The eVACUATE system performance and scalability will be validated in four distinct scenarios involving incidents with large crowd at various venues with the requirements of evacuation time reductions and increases of safety and security. These are: 1) Underground stations in Bilbao; 2) Real Sociedad Footbal Stadium in San Sebastian, 3) Athens International Airport and 4) a STX Cruiseship.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Call for proposal
FP7-SEC-2012-1
See other projects for this call
Funding Scheme
CP-IP - Large-scale integrating projectCoordinator
11526 Athina
Greece
See on map
Participants (18)
SO17 1BJ Southampton
See on map
106 82 ATHINA
See on map
8232 JN Lelystad
See on map
15561 ATHINA
See on map
20600 Eibar Guipuzcoa
See on map
190 19 SPATA
See on map
00156 ROMA
See on map
BA2 3DQ Bath
See on map
28108 Alcobendas Madrid
See on map
3000 Leuven
See on map
13857 AIX EN PROVENCE
See on map
10129 Torino
See on map
44600 Saint Nazaire
See on map
01069 Dresden
See on map
09111 Chemnitz
See on map
20014 DONOSTIA SAN SEBASTIAN GUIPUZCOA
See on map
48001 Bilbao
See on map
20123 Milano
See on map