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Completed H2020 European Commission

A Holistic Fire Management Ecosystem for Prevention, Detection and Restoration of Environmental Disasters

€22.79M EUR

Funder European Commission
Recipient Organization Rise Fire Research As
Country Norway
Start Date Dec 01, 2021
End Date May 31, 2025
Duration 1,277 days
Number of Grantees 53
Roles Participant; Third Party; Coordinator
Data Source European Commission
Grant ID 101036926
Grant 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.

All Grantees

Diputacion de Avila; Fundatia Pentru Smurd; Ethniko Kentro Erevnas Kai Technologikis Anaptyxis; Electric Aircraft Concept; Schmitz One Seven Gmbh; Otto-Von-Guericke-Universitaet Magdeburg; Universitat de Girona; Tecnosistem Spa; Jotne Connect As; Federacion de Asociaciones Forestales de Castilla Y Leon; Apokentromeni Dioikisi Kritis; Agenzia Campana Per la Mobilita Leinfrastrutture E Le Reti; Polytechneio Kritis; Comune Di Sorrento; Software Imagination & Vision Srl; Universita Degli Studi Di Napoli Federico Ii; Rise Research Institutes of Sweden Ab; Rina Consulting Spa; Johanniter Osterreich Ausbildung Und Forschung Gemeinnutzige Gmbh; Drone Hopper Sl; Squaredev; Feischl Richard; Frontier Innovations I.K.E.; Innov-Acts Limited; Lietuvos Agrariniu Ir Misku Mokslu Centras; Disaster Competence Network Austria; Copenhagen Business School; Asociatia Forestierilor Din Romania Asfor; Ecosat Airships Sl; K3Y; Adrestia Erevnitiki Idiotiki Kefalaiouxiki Etaireia; Vipo As; Maggioli Spa; Bundesanstalt Fuer Materialforschung Und -Pruefung; "National Center for Scientific Research ""Demokritos"""; Sviluppo Tecnologie E Ricerca Per L'Edilizia Sismicamente Sicura Ed Ecosostenibile Scarl; Capgemini Espana Sl; Danmarks Tekniske Universitet; Woodify As; Freiwillige Feuerwehr Gumpoldskirchen; Engineers for Business Ipiresies Technologias Kai Michanikis Anonimi Etairia; Mediterranean Agronomic Institute of Chania; Pompiers de L'Urgence Internationale; Rise Fire Research As; Fundacion Cartif; Ethniko Asteroskopeio Athinon; Global Biodesign Scomm; Acceligence Ltd; Eight Bells Ltd; Stadt Graz; National Taiwan University of Science and Technology; Universidad de Salamanca; Ministerul Mediului, Apelor Si Padurilor

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