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Forest surveillance with artificial intelligence and digital technologies - FORSAID

Project description

Digital technologies to safeguard forest health

Forests play a critical role in achieving the objectives of the European Green Deal, yet forest trees are increasingly threatened by invasive pests. The EU-funded FORSAID project will develop digital technologies for early detection of forest pests, monitoring their occurrence, and providing data to manage their spread effectively. The project will leverage the Internet of Things (IoT) to deploy networks of insect traps across forests, employing deep learning to analyse images transmitted remotely. Additionally, FORSAID will test robotic devices for automatic barcoding of captured pests and drones equipped with sensors to assess plant health status. AI and machine learning models will be developed to distinguish between various types of stress affecting forests.

Objective

Forests have an important role in the achievement of the objectives of the European Green Deal. Forest trees are increasingly threatened by invasive pests, with many of them being regulated in the Union territory. FORSAID has as an overall goal to develop a comprehensive combination of innovative digital technologies aimed at detecting regulated forest pests at an early stage, surveying their occurrence in the territory, and providing essential information for the adoption of phytosanitary measures to limit their spread and impacts. The project adopts a multi-actor and multidisciplinary approach tailored to develop and favour the adoption of digital technologies at different spatial and temporal scales associated with a selected list of important regulated forest pests. The Internet of Things (IoT) will be used to create networks of insect traps for major guilds of insects, thanks to innovative deep learning analysis of images sent remotely from the traps. Robotized devices will be developed and tested for the automatic barcoding of the captured pests. Drones equipped with sensors will be used for the scanning of plant health status through the measure of physiological variables. Remote sensing techniques will be used to validate existing ground-truth data on the occurrence of tree alterations associated with abiotic and biotic factors, and models based on Artificial Intelligence (AI) and machine learning (ML) will be developed to discriminate different types of stresses as soon as they appear. An economic analysis will address the costs and benefits of using digital technologies for the detection and surveillance measures, considering the economic, environmental, and social impacts of regulated pests in EU forests. Stakeholders from the forest sector will be involved in a multi-actor approach to drive the research to applicable results and co-construct guidelines for the best use of new digital technologies for forest pest detection and monitoring.

Fields of science (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-CL6-2023-GOVERNANCE-01

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Coordinator

UNIVERSITA DEGLI STUDI DI PADOVA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 631 250,00
Address
VIA 8 FEBBRAIO 2
35122 Padova
Italy

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Region
Nord-Est Veneto Padova
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 631 250,00

Participants (15)

Partners (1)

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