KIRAS Security Research

  •  11
Kooperative Projekte > 2014

LEAL

Airborne detection and contextual analysis of dynamic situation reports in crisis scenarios

In crisis situations, it is particularly important to quickly get an overview of the situation. The more accurate and quickly available this overview, the safer and faster the most important, first emergency steps.

Focus of this project is the use of unmanned aerial vehicles (UAV) for rapid creation of the overview of the situation in critical situation. Among the possible scenarios are traffic accidents, large fires, and industrial accidents, but also crime scenes. In the latter scenario, documentation purposes are more important. The overview of the situation, i.e. the model, is created by using optical sensors in the visible and infrared light range which are integrated into the UAV. In addition to the sensor from the air laser scanners will be used to enhance accuracy of the model by details which are not visible from the air or not accurate enough to measure.

The UAVs, launched from large distance, can be quickly on-site and already observe the area on their way there, in real-time. The interpretation of the sensor data includes a contextual analysis of the scene, for example, the detection and evaluation of symbols indicating dangerous goods, determining the degree of destruction of the vehicles involved, people detection, determining the fastest route to the accident (e.g. if the emergency lane is blocked). Thus, an immediate decision support for selecting the best rescue or evacuation procedures is provided. In case of documentation of accidents or crime scenes the model is a centimeter-accurate representation of the scene. This allows high precision surveys of the scene, even in retrospect.

A special feature of the user experience should be the semi-autonomous flight control system that will give the operator in crisis and stress situations the particularly important freedom to concentrate on the actual application and not on piloting the UAV. Basis of traffic research is data collection after accidents and the associated electronic data processing. Providing the input data is very complex, thus, in this project we will use the model to be able to do that automatically. Information, extracted from the model should also be integrated into existing training tools to, on the one hand, create an even more realistic simulation, and on the other hand to improve mission planning. Together with the industry partners and the public agencies, the results will be evaluated on the basis of typical application scenarios. In addition, we expect the sensing and analysis system to have high economic potential in traffic, safety but also in industry applications.

Project Coordinator
Christoph Sulzbachner, AIT Austrian Institute of Technology GmbH

Project Partners
RIEGL Research Forschungsgesellschaft mbH

FH Joanneum Gesellschaft mbH

EYE.AERO GmbH

LKR Leichtmetallkompetenzzentrum Ranshofen GmbH

Schild & Partner GmbH
Bundesministerium für Inneres (BMI)

Contact
Christoph Sulzbachner
Senior Engineer

Digital Safety & Security Department
Safe and Autonomous Systems

AIT Austrian Institute of Technology GmbH
Donau-City-Straße 1,
1220 Vienna, Austria

T +43 (0) 50550-4177,
M +43 (0) 664 8251342,
F +43 (0) 50550-4150

christoph.sulzbachner@ait.ac.at 
http://www.ait.ac.at