About the project

EU-SENSE (European Sensor System for CBRN Applications) is a research and innovation project with time duration of 36 months. The EU-SENSE consortium consolidates 9 organizations and puts effort in increasing the real capabilities of European CBRN practitioners. The key aspect of the EU-SENSE project is the response to actual needs of European practitioners and technological gaps identified by the ENCIRCLE project, which remains in close collaboration with the EU-SENSE project. The crucial innovation of the EU-SENSE project is the development of a novel network of chemical sensors consisting of heterogeneous sensor nodes supported with cutting-edge machine-learning and dispersion modelling.

Key objectives

  • 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.
  • 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.
  • 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.

EU-SENSE solution

  • Creation of advanced network of sensors combining heterogeneous sensor nodes
  • Sensor node comprising a range of chemical detection technologies including IMS, FPD and MO detector array sensors
  • Adaptable sensor nodes, which can operate as a stationary or person-worn units
  • Application of machine-learning and dispersion modelling
  • Dedicated data model enabling interoperability and scalability of the network
  • Training module of the system for the practice of end users
  • Fully operational solution tested in realistic conditions (in a professional firefighter training facility)

Innovation

  • Reduction of false alarms through machine learning of environmental noise:
    • Clutter (or naturally existing noise in the environment) affects the readouts of the chemical sensors, which may result in a higher number of false alarms. The aspect of clutter and its influence on sensor readouts has not been given much attention in state-of-the-art systems.
    • EU-SENSE applies machine-learning based anomaly detection method for reduction of false alarms.
  • Improvement of situational awareness through dispersion modelling of the hazardous substances:
    • The EU-SENSE system will apply inverse modelling that will allow for quick and precise threat source location. The algorithm will notify about the set of potential threat source locations as soon as the threat is detected and network collects first positive readouts. Subsequently, the outcome will be improved based on the incoming sensors measurements.
    • The system will also be able to predict possible dispersion routes of the hazardous substance over time by the application of ensemble forward modelling. This information will facilitate the application of appropriate countermeasures and speed up the identification of safe evacuation routes.
  • Live demonstration of fully operational solution in professional Polish Firefighter training facility in Zamczysko Nowe
    • The EU-SENSE system, including all functional software components and heterogeneous sensor nodes will be tested with the use of chemical simulants.
    • The demonstration will be performed in realistic operational conditions with the involvement of firefighters including specialised chemical rescue unit.
    • Prior to the demonstration, a comprehensive training session will be held, where theinvolved personnel will have the opportunity to familiarize with the equipment and the system.

About the project

EU-SENSE (European Sensor System for CBRN Applications) is a research and innovation project with time duration of 36 months. The EU-SENSE consortium consolidates 9 organizations and puts effort in increasing the real capabilities of European CBRN practitioners. The key aspect of the EU-SENSE project is the response to actual needs of European practitioners and technological gaps identified by the ENCIRCLE project, which remains in close collaboration with the EU-SENSE project. The crucial innovation of the EU-SENSE project is the development of a novel network of chemical sensors consisting of heterogeneous sensor nodes supported with cutting-edge machine-learning and dispersion modelling.

Key objectives

  • 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.
  • 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.
  • 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.

EU-SENSE solution

  • Creation of advanced network of sensors combining heterogeneous sensor nodes
  • Sensor node comprising a range of chemical detection technologies including IMS, FPD and MO detector array sensors
  • Adaptable sensor nodes, which can operate as a stationary or person-worn units
  • Application of machine-learning and dispersion modelling
  • Dedicated data model enabling interoperability and scalability of the network
  • Training module of the system for the practice of end users
  • Fully operational solution tested in realistic conditions (in a professional firefighter training facility)

Innovation

  • Reduction of false alarms through machine learning of environmental noise:
    • Clutter (or naturally existing noise in the environment) affects the readouts of the chemical sensors, which may result in a higher number of false alarms. The aspect of clutter and its influence on sensor readouts has not been given much attention in state-of-the-art systems.
    • EU-SENSE applies machine-learning based anomaly detection method for reduction of false alarms.
  • Improvement of situational awareness through dispersion modelling of the hazardous substances:
    • The EU-SENSE system will apply inverse modelling that will allow for quick and precise threat source location. The algorithm will notify about the set of potential threat source locations as soon as the threat is detected and network collects first positive readouts. Subsequently, the outcome will be improved based on the incoming sensors measurements.
    • The system will also be able to predict possible dispersion routes of the hazardous substance over time by the application of ensemble forward modelling. This information will facilitate the application of appropriate countermeasures and speed up the identification of safe evacuation routes.
  • Live demonstration of fully operational solution in professional Polish Firefighter training facility in Zamczysko Nowe
    • The EU-SENSE system, including all functional software components and heterogeneous sensor nodes will be tested with the use of chemical simulants.
    • The demonstration will be performed in realistic operational conditions with the involvement of firefighters including specialised chemical rescue unit.
    • Prior to the demonstration, a comprehensive training session will be held, where theinvolved personnel will have the opportunity to familiarize with the equipment and the system.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 787031.

Project Coordinator: Łukasz Szklarski, PhD
ITTI Sp. z o.o. Poznań, Poland
e-mail: lukasz.szklarski@itti.com.pl