CBRN CLUSTER – PART B PROJECTS 2017 CALL
From 2018 to 2021
Coordinator: ITTI Sp. z. o.o. – Poland
- ITTI Sp. z. o.o. – Poland
- Netherlands Organisation for Applied Scientific Research (TNO) – Netherlands
- Swedish Defence Research Agency (FOI) – Sweden
- Norwegian Defence Research Establishment (FFI) – Norway
- Technisch-mathematische studiengesellschaft mbh (TMS) – Germany
- The Main School of Fire Service (SGSP) – Poland
- Airsense Analytics (AS) – Germany
- University of Warsaw (UW) – Poland
- Police Service of Northern Ireland (PSNI) – Northern Ireland
The project has three high level objectives such as:
- High Level Objective 1 – To contribute to better situational awareness of the CBRNe practitioners through the development of a novel network of chemical sensors, which will provide a technological solution to relevant gaps presented in the ENCIRLCE catalogue of technologies.
- High Level Objective 2 – To improve the detection capabilities of the novel network of chemical sensors through the use of machine learning algorithms to reduce the impact of environmental noise and the application of contaminant dispersion models.
- High Level Objective 3 – To showcase the usability of the EU-SENSE network to CBRNe practitioners in order to validate the system and to maximize its exploitation potential. The objective also entails the preparation of training sessions with CBRNe practitioners in relevant conditions.
In more depth, the EU-SENSE proposes the design and development of a sensor network system, which will allow for improved chemical detection. The network will incorporate commercially available stationary and person-worn sensors, which will constitute heterogeneous sensor nodes. These nodes will comprise sensors incorporating various detection technologies. The application of heterogeneous sensor nodes will allow for detection of a large spectrum of chemical agents. The overall performance of the network will be enhanced with novel data fusion algorithms. Moreover, the fundamental part of the EU-SENSE system will focus on network performance improvement and false alarm reduction via data fusion algorithms including machine learning of the environmental noise and contamination modelling.
In addition, the proposed system will feature a training mode, which will support end users in their training sessions. The training mode will aid users in familiarization with the system, practicing and rehearsing for a specific scenario/incident and help in decision making process thanks to source location estimation and hazard prediction. The training component will be supported by synthetic data defined within the pre-defined scenarios. The synthetic data will be influenced by modelling and machine learning tool to reflect realistic substance distribution in the environment and to make allowances for naturally existing background noise (clutter).
TERRIFFIC – Tools For Early and Effective Reconnaissance in CBRNE Incidents Providing First Responders Faster Information and Enabling Better Management of The Control Zone
From 2018 to 2021
Coordinator: ARKTIS Radiation Detectors – Switzerland
- ARKTIS Radiation Detectors – Switzerland
- Commissariat à l’énergie atomique et aux énergies alternatives (CEA) – France
- TL&A – France
- Luxembourg Institute of Science and Technology (LIST) – Luxembourg
- Ecole Centrale de Lyon – France
- ARTTIC – France
- Bruhn NewTech – Denmark
- ISEM-Institut pre Medzinarodnu Bezpecnost a Krizove Riadenie N.O. – Slovakia
- AERACCESS – France
- NEXTER Robotics – France
The TERRIFFIC project will deliver a step change in the effectiveness of first responders during the first hours of a Radiological, Nuclear, explosive (RNe) incident. It will lead to reduced response time, less health and safety risks for the response team, and less human intervention in the operation due to higher number of automated processes and extended mobile detection capabilities. TERRIFFIC will enrich the European response to RNe events by a set of modular technology components in a comprehensive system, incl. new detectors, algorithms, drones, robots, dispersion models, information management software and decision support systems. The project will provide detailed information on the applicability of some developments within a chemical and biological (C/B) context. Dedicated Key Performance Indicators will measure the progress towards targeted performance goals, such as significant acceleration of the time to start terrain interventions due more accurate and near-to-real-time estimation of the control and exclusion zones. Advanced mixed reality technology will be leveraged to provide first responders with ad-hoc available and continuously updated information during operations. TERRIFFIC is SME-led and practitioner-driven. Leading edge technologies will be provided by the R&D partners, whereas key innovative components will be developed by SMEs already involved in military or first responder markets taking on the commercialisation of the TERRIFFIC System and its components. The practitioners will be strongly involved throughout the development process, components assessment and technology trialling. The project will leverage results from previous successful FP7 projects, closely cooperate with ENCIRCLE on the CBRN Cluster and market aspects, and with eNOTICE on training and technology testing and assessment. Special attention will be given to standardisation to optimise the integration with future and already applied solutions.
cordis / project website
From 2018 to 2021
Coordinator: Lingacom Ltd – Israel
- Sociedad Europea de Analisis Diferencial de Movilidad SL – Spain
- Atos Spain SA – Spain
- TECHNION – Israel Institute of Technology (IIT) – Israel
- Ben-Gurion University of the Negev – Israel
- Dutch Customs Administration – Netherlands
- S2 Albania Sh.p.k. – Albania
- Ministerio del Interior – Guardia Civil – Spain
- Agencia Estatal Consejo Superior Deinvestigaciones Cientificas – Spain
The threat of CBRNE (Chemical, Biological, Radiological, Nuclear and Explosives) components used by terrorists is major concerns for EU and worldwide security. Today there is a major security gap in the existing security flow that can be used by terrorists to hide and smuggle CBRNE materials inside containers and vehicles. The challenge of improving container and vehicles border crossing and critical infrastructure entrance security checks is of great importance in fighting terrorist threats, theft and smuggling. Improvised Nuclear Device (IND) could be detonated using nuclear weapon components, modified nuclear weapons, or a self-made device and Radiological Dispersal Device (RDD) could be designed to disperse radioactive materials through an explosion (or ‘dirty bomb’).It was also reported that since 1998, in the US alone, there have been more than 1,300 reported incidents of lost, stolen, or abandoned devices containing sealed radioactive sources, an average of about 250 per year. Chemical and Biological are in use by terrorists. Report of Wm. Robert Johnston summarizes the “historical attacks using chemical or biological weapons” with 23 attacks since 1994, while all the recent attacks were done mainly by terrorists and the Syrian militants. The attacks demonstrating the attempts and capability of terrorists to acquire chemical and biological materials (chlorine, mustard, sarin, etc) and to prepare chemical or biological bombs. COSMIC system plans to bridge the major security gap for fast inspection of large number of containers and vehicles in sea port and in crossing borders for CBRNE materials. COSMIC’s technology can be adapted also to air containers. COSMIC proposes a novel technological approach for the detection of CBRNE materials hidden in shipping containers. COSMIC project includes the research, design and implementation of a three stage (primary, secondary, focused manual inspection) detection system using new set of innovative sensors