Real-time localisation and real-time monitoring of first responder team members

Localisation of first responders is vital for the responder’s safety, especially in GNSS-denied environments. The responders need to localise each team member in risky situations to rescue them or notify other members near potential hazardous and risky situations. According to the project responder PR4 study, most of the responders send their location by using hand-held radios (inefficient procedure, especially in dense smoke) instead of automated realtime indoor localisation systems. In fact, a continuous indoor/outdoor localisation system will provide the location of first responders outside, in buildings, above and below the ground in real-time. In addition, a body motion analysing system will provide position and orientation of the responders (e.g., standing still, walking or lying on the ground). Furthermore, a wearable health monitoring system will provide information about the vital activity and status of responders. An overall in-team-system, integrating indoor/outdoor localisation, body posture capture and health monitoring will provide a complementary solution for situational awareness within team-members, thus filling the current gaps. The Capability Gap 1 is fulfilled by WP7 (Team Monitoring System).

Detection of Surrounding Risks and Threats

According to the PR4 study, there is a lack of sensor systems efficiently running in the responder teams. The first responders mainly prepare necessary and required tools and materials for the emergency in the preparedness phase. However, the information setup in this phase is full of fragmentary, incomplete and sometimes wrong information. In addition, the situation in the field can rapidly evolve in time, generating new hazards, currently impossible to detect and forecast. For example, a terrorist attack can only be realised after the first responders arrive in the field and rapidly evolving chemical risks cannot be detected and forecasted in the preparedness phase. Thus, there is a need for various types of sensor systems to detect, identify and monitor threats for responders to be well prepared against unexpected emergencies. These gaps are fulfilled by sensor systems defined in WPs (from WP3 to WP6).

Information Fusion and Comprehensible User Interfaces

Simultaneous and intense data flow from heterogeneous sources should be fused to obtain reliable information for first responders. The fused data will be provided to operational centre and responders in the field. Furthermore, Artificial Intelligence (AI) will be used to detect, identify and classify the threats and anomalies surrounding the first responders to generate detailed common situational awareness picture. It is important to provide detailed picture, which is generated by fusing the information gathered by the sensor systems in the field, for the dispatchers in the incident management centre. This gap is fulfilled by TeamAware software platform (WP10) combining all sensor systems (from WP3 to WP6) as well as a non-traditional way of obtaining further data such as social media, citizens in the incident and IoT infrastructure of the city (WP8). All kind of sources are connected with a redundant communication network (WP9). The intensive data flow and fused information in the situational awareness picture can exceed the cognitive limits of the responders in the field. In detail, the layered dash-boarding of information should be clear, understandable and manageable for the responders in the operation. Thus, there should be user interfaces (UIs) enhanced with Augmented Reality (AR) to present refined information to the responders. This gap is fulfilled by Human Machine Interface (HMI) displaying refined, filtered, and manageable common situational awareness picture (WP11)


Monica Florea
Administrative Coordinator

European Projects Department
Soseaua Bucuresti-Ploiesti 73-81 COM


Çağlar Akman
Technical Coordinator

Command and Control Systems
Eskişehir Yolu 7 km


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101019808.

© 2021 | TeamAware All Rights Reserved