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Tools for early and Effective Reconnaissance in cbRne Incidents providing First responders Faster Information and enabling better management of the Control zone

Periodic Reporting for period 2 - TERRIFFIC (Tools for early and Effective Reconnaissance in cbRne Incidents providing First responders Faster Information and enabling better management of the Control zone)

Reporting period: 2019-11-01 to 2021-10-31

TERRIFFIC set out to develop technologies that would deliver a step change in the effectiveness of first responders during the 30 to 60 minutes of a Radiological, Nuclear, and/or explosive (RNe) incident. TERRIFFIC will help to enrich the European response to RNe events by integrating a set of complementary, interconnected and modular software and hardware components into an integrated system. These components include new detectors and sensors, algorithms, drones, robots, dispersion models, augmented reality, information management software and decision support systems. The TERRIFFIC System will provide first responders with continuously updated information during operations, available on an ad hoc basis, saving the lives of both first responders and the general public. Leading edge technologies have been provided by the R&D partners, whereas key innovative components have been developed by SMEs already involved in military or first responder markets taking on the commercialisation of the TERRIFFIC System and its components.

The project has focussed on developing technology to assist first responders dealing with an explosion containing radioactive or nuclear elements, but has also addressed the applicability of some of the components’ developments within a chemical and biological (C/B) context. The project has succeeded in delivering a System with an overall Technology Readiness Level (TRL) 6/7 and further post-project improvements will be necessary for the full System to reach the market.
TERRIFFIC partners have established a close and regular dialogue with practitioners through bi-lateral interviews, interactive workshops and during on field trials. This enabled solution providers to gain a better understanding of the needs of practitioners during the first 30–60 minutes of an RNe event. As a result of early discussions with practitioners and the first Semi-Public Workshop, we were able to define the specifications of the TERRIFFIC system, as well as those of each of its components in terms of robustness, endurance, performance, but also maintenance of operational capability. This knowledge was used to develop the technologies to meet the requirements of CBRNe practitioners.

A total of four trials were held in the project with fire and police officers from France, the Czech Republic and Slovakia. The first two trials in April and May 2019 provided opportunities to assess the core components in the TERRIFFIC system and to establish a strong baseline, from which future development and integration work could progress. Towards the end of the project a Field Exercise and the Final Trial were held to assess how the System performed operationally using real radiation sources in a variety of challenging scenarios. The System was tested against legacy systems to assess its value operationally. The results showed clearly that using TERRIFFIC could save valuable time and using technology to ascertain the type, size and location of the risk meant that first responders did not need to be sent into the high risk area until more accurate information had been gathered.

Two further Workshops were held, providing opportunities for partners to share details and assessments of their work to a wider CBRNe audience. The first was held virtually in December 2020, whilst the final Public Workshop was a hybrid meeting with delegates attending in person at Entente Valabre, near Aix-en-Provence in France, and others joining remotely. The results of the project have also been disseminated via scientific publications, presentations at international conferences, European Commission workshops, the project website, six videos, in the specialist media and on LinkedIn and Twitter.

Developed in the project have been:
• The world's smallest gamma camera, weighing less than 300g, which can be mounted on the adapted drone and robot, together with the SiPR detector
• A new handheld beta detector, which can measure beta contamination in a high gamma background
• Plume modelling software that can identify the location and type of source and its likely spread taking into account prevailing weather conditions
• Augmented reality software using either an Apple iPad and Microsoft Hololens
• Incident management system that assimilates all of the data from the sensors into one place for the incident commander
The key components of the Terriffic System are:
• Aeraccess’ Hawker Q800X is a versatile UAV platform that can carry a wide range of different payloads up to 1kg, including the RNe sensors and cameras developed in the project. Designed to resist harsh weather conditions, it can be flown in winds of up to 70 kph with gusts of 90 kph and can still operate in heavy rain conditions, snow, fog and desert conditions.
• The NERVA XX robot from Nexter Robotics is a light, robust and versatile UGV, which can be equipped with more than 20 different mission kits, delivering significant flexibility to users. It is used operationally for tasks as varied as CBRN recognition, IED control and victim assistance. Here it is being deployed with the world’s smallest coded aperture gamma camera and the FPG detector.
• Arktis Radiation Detectors is expanding the functionality of its mobile radiation monitoring MODES van to ‘house’ the full Terriffic System, providing rapid deployment. It has also developed a SiPR detector and a Flat Panel Gamma (FPG) detector, which delivers the highest degree of sensitivity at a specificity sufficient to discern the type of radioactive source (medical, natural, nuclear, industrial).
• CEA List is developing the world’s smallest coded aperture gamma camera, which visualises any contamination hot spots. Weighing only approximately 300 grammes, it can be fitted to the UAV and the UGV and transmits the images back to the incident management software. In training mode, it simulates the gamma camera behaviour without using any radioactive sources, offering further tangible benefits to practitioner organisations.
• The École Centrale de Lyon has developed the algorithms and software that are used not only to locate the radiation source, but also to identify what the source is and how it will disperse into the area, depending on weather conditions and surrounding buildings. The measurements taken produce a plume model, which can be viewed in a 3D simulation of the contaminated area.
• The augmented reality solution developed by Luxembourg Institute of Science and Technology will provide a never before seen set of information in near real-time to the incident commander, delivering essential data from inside the red zone. Commanders can visualise the incident, overlay various symbols and see the sensor readings incorporated into the visual graphics.
• Bruhn NewTech’s CBRNe-Frontline incident management system pulls all of the data from the System into one place, including from the radiation sensors and cameras that are mounted on the UAV and UGV and the results of the plume modelling forecasting. Offering full situational awareness, the real-time status and management of all sensors is coordinated through the embedded SCIM® software hub. Supporting critical decision making, the System can communicate a CBRNe picture to command and control systems enabling the safeguarding of lives. CBRNe-Frontline is already in operational use by NATO forces, giving it proven credentials.
L-R Arktis’ MODES van, CBRNe-Frontline from Bruhn NewTech, AR solution from LIST
Logo of the TERRIFFIC project
Montage image from the Field Exercise in Slovakia
Montage image from the final Public Workshop and Fire Congress demonstration
L-R CEA’s miniaturised gamma camera, radioactive source identified, ECL plume modelling software
L-R Arktis’ SiPR detector, Aeraccess Hawker Q800X drone, Nexter’s NERVA XX