Innovative Training & Decision Support for Emergency operations

Abstract

The INDIGO project aims to research, develop and validate an innovative system integrating the latest advances in Virtual Reality and Simulation in order to homogenise and enhance both the operational preparedness and the management of an actual complex crisis. INDIGO will enable: (a) the 3D interactive and realistic visualisation of the complete crisis environment, including data coming from the field, simulation results, and building interiors; (b) the creation and simulation of different evolving scenarios for planning, training, and anticipating future states and impending developments during operations, and analyse events after the crisis; (c) the simultaneous training of decision makers, crisis managers as well as first responders that will be influenced by the simulated scenario and that will reciprocally influence its evolution; (d) the involvement of multiple participants, thanks to its distributed architecture, while offering a unique pictorial way of sharing and communicating complex knowledge across organisation boundaries. In addition, INDIGO will propose a European emergency symbology reference for 2D/3D maps. This will fill an important gap by offering a common visual reference that can be used across Europe to facilitate the immediate understanding of the situation, thus improving decision making across organisational boundaries. The definition of the functional specifications of the system will be driven by the analysis of the needs of real end-users participating in the project as partners or involved in the User Group. These organisations will test and validate the outcomes of the project with real-world scenarios. By the end of the project a packaged system integrating all the proposed technologies will have been developed and provided to them under two versions for purpose of validation and refinement of needs and specifications. CRS4, together with ISTI-CNR, will concentrate on extending such a framework with the possibility of handling two particularly important data types: extremely massive point clouds, and geo-referenced (three-dimensionalized) photographs. These two particular datatypes are of particular importance to the security domain, since they can be acquired very rapidly and provide both measurable and visually recognizable description of a site. On the server side, the focus will be on the efficient handling of extremely massive data, on the incorporation of raw data (e.g., from LIDAR acquisitions), and on the efficient compressed streaming. Moreover, a combined (hybrid) solution using both 3D points and images will be researched.