Summary
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, DRYADS 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 DRYADS 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, DRYADS will use alkali activated construction materials (AAM) integrating post-wildfires wood ashes (PWA) for fire-resilient buildings and infrastructure. DRYADS 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 DRYADS 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, DRYADS 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. DRYADS 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.
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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/101036926 |
Start date: | 01-12-2021 |
End date: | 31-05-2025 |
Total budget - Public funding: | 22 748 947,00 Euro - 19 258 995,00 Euro |
Cordis data
Original description
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.Status
SIGNEDCall topic
LC-GD-1-1-2020Update Date
27-10-2022
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