• ACRONYM: TeamAware.
  • TITLE: Team Awareness Enhanced with Artificial Intelligence and Augmented Reality.
  • SUMMARY: TeamAware aims to develop an integrated and cost-efficient situational awareness system for first responders from different sectors to enhance crisis management, flexibility and reaction capability through real-time, fused, refined, and manageable information by using highly-standardised augmented reality and mobile human machine interfaces.


First responders are the groups of people, services and organisations with specialised skills and qualifications whose duty is to arrive first to the emergency zone, carry out search, save and rescue operations, and perform crisis management in natural or human-made disasters. Although first responders enable secure and safe societies by protecting the communities, responding to the disasters and rescuing lives, they often use inefficient, weak and obsolete technologies in their operations.

Operational capabilities of the first responders can be dramatically boosted by the advances in technology and engineering fields such as smart sensor systems, wearables, data processing, data fusion, data analytics, communication infrastructure, and artificial intelligence tools. In this context, TeamAware will bring together and integrate different types of sensor units (including drone-mounted, wearable, and external sensor systems, existing first responder services, and operation centres) as a first step to develop a resilient, interoperable and user-friendly system that will merge and process data streams coming from the heterogeneous sources to provide an accurate and real-time situational awareness picture. This information will support operations at the command & control centre as well as field responders, who will take advantage of the latest technologies in visual understanding and communications.

TREE’s main role in TeamAware is threefold: (1) we lead the work package on user requirements and architecture definition and design; (2) we contribute to dynamic scene understanding by using Artificial Intelligence techniques for the analysis of videos and images in real time; and (3) we define the validation scenarios for all the elements and subsystems that build up the overall solution.


  • BUDGET: €6,964,702.50
  • DURATION: 36 months (01/05/2021 – 30/04/2024)
  • PROGRAMME: H2020-SU-DRS-2020
  • PROJECT COORDINATOR: Simavi – Software Imagination & Vision 



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

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