A Holistic Fire Management Ecosystem for Prevention, Detection and Restoration of Environmental Disasters
Considering the socio-ecological transition of Europe 2030, and towards a more resilient and informed community, focusing on the forests that are near wildfire risk, TREEADS aims to build upon state-of-the-art high TRL products and unite them in a holistic Fire Management platform that optimize and reuse per phase the available Socio-technological Resources in all three main phases of Wildfires.
For the prevention and preparedness TREEADS propose the use of a real-time risk evaluation tool that can receive multiple classification inputs and work with a new proposed neural network-powered Risk factor indicator.
To create a model of Fire adapted communities (FAC) in parallel to insurance incentives, TREEADS will use alkali activated construction materials (AAM) integrating post-wildfires wood ashes (PWA) for fire-resilient buildings and infrastructure. TREEADS also uses a variety of technological solutions such as the Copernicus infrastructure, and a swarm of small drones customized for accurate forest supervision. In the area of Detection TREEADS propose a variety of toolsets that will accommodate most needs. Stemming from Virtual reality for the training, wearables for the protective equipment of the emergency responders. to UAV (drones), UAG and airships for improving capacity in temporal and spatial analysis as well as to increase the inspected area coverage.
Last, TREEADS will build a new land and field-based restoration initiative that will use all modern techniques such as agroforestry, drones for seed spread, Internet of things sensors that will be able to adapt the seeding process based on the ground needs and on the same time with the help of AI to determine post-fire risks factors. TREEADS solution will be demonstrated and validated under real operating conditions.
Demonstration will involve Eight complex pilot implementations executed in seven EU countries and in Taiwan.
Aiming at addressing the uncertainty and socio-economic dimensions inherent in wildfire management, and to minimize the impact of wildfires through timely and informed decision-making, our research introduces an architectural framework for a software platform for Detection of Emerging Fire-related Situations and Response Process Management. The platform digests real-time and heterogeneous data from a variety of sources (i.e. meteorological stations, environmental sensors, satellite-based fire detection services and AI-processed UAV photographs), to continuously assess and predict critical situations.
Current conditions are repeatedly monitored and juxtaposed to fire propagation simulation scenarios and event patterns pre-defined with the active involvement of domain experts. Depending on those contextual cues, analytics algorithms leveraging similarity metrics trigger fire response workflows. Those have been accordingly elicited from the main crisis management actors such as local authorities, firefighters, wildlife administrators and environmental engineers fostering stakeholder engagement and collaborative wildfire response efforts.
The analysis results as well as additional information, such as animals or vehicles in danger as detected by visual recognition algorithms on UAVs, are then redirected to a variety of user interfaces, such as map-equipped dashboards, mobile applications, AR-enabled helmets, or simple text messaging systems.
TREEADS Facts & Figures
Project name: A Holistic Fire Management Ecosystem for Prevention, Detection and Restoration of Environmental Disasters
Grant Agreement No: 101036926
Topic: LC-GD-1-1-2020 - Preventing and fighting extreme wildfires with the integration and demonstration of innovative means
Duration: 1/12/2021 – 31/05/2025
EC Contribution: € 19 258 995,18