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