CBRN CLUSTER – PART B PROJECTS 2017 CALL
EU-SENSE – European Sensor System for CBRN Applications
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).
cordis / project website
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