INTREPID

First responders face many threats and challenges in the earliest phases of a natural or man-made disaster. They must deal with pressing and often dramatic demands in a chaotic, dangerous and extremely dynamic environment. Victims and inhabitants need assistance while the situation is still perilous, and much-needed resources are simply not available. They must locate and rescue victims, guide people, neutralise threats, and prevent additional collateral damage. Those tasks become very difficult especially in densely populated yet hard-to-reach areas, which are risky to access and impossible to oversee. The lack of reliable information and the deep uncertainty about the current situation present real obstacles to a quick and effective response. When time is of the essence, enhanced situational awareness is vital to make smart decisions that save lives and minimise environmental damage. A rapid assessment of a complex site with many unsafe pockets is difficult and cumbersome with today’s technologies. Information about the location of victims, hazardous areas, threats and ongoing rescue operations (self-organizing citizens) must be gathered from the disaster zone. The incoming information is usually scattered and unconfirmed, which undermines and slows down the response while increasing the risks for first responders who do not understand the dangerous environment they are entering. Incorrect information may well set the first responders on the wrong course, endangering lives and increasing the

impact of the ongoing crisis.

INTREPID will develop and validate a state-of-the-art, easy-to-deploy, secured and user friendly platform employing Intelligence Amplification combined with eXtended Reality concepts and innovative autonomous cybernetic assistants to enhance the speed, range, and effectiveness of first responders, with particular focus on the safe exploration and assessment of complex and hazardous zones.

INTREPID aims to revolutionize first responder operations in the earliest phases of a disaster when the chances to save lives are highest and operations are slowed by many types of uncertainties.

Consortium

CS Group
Totalförsvarets forskningsinstitut
Technical University of Munich
Centre for Research and Technology Hellas
Vrije Universiteit Brussel
CrisisPlan
ETELM
ALX Systems
Robotnik
Inconito
Belgian Federal Police – Directorate of Special Units
Ville de Marseille – Bataillon de Marins-Pompiers de Marseille
Greater Stockholm Fire Brigade
Madrid Police
Servicio Madrileno De Salud – Servicio de Urgencias
Escuela Española de Salvamento y Detección con Perros
UK International Search and Rescue