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Real-time automatic monitoring and ML-based prediction of pest insects

Project description

Smart solutions for pest management

Farmers face a major challenge with pest management, which can devastate crop yields and threaten food security. Traditional methods are often reactive, leading to losses and increased pesticide use. This approach not only impacts the environment but also farmers’ profits. To tackle this issue, the EIC-funded xTrap project offers a smarter solution for pest management in the Agriculture 4.0 era. Specifically, it combines real-time monitoring with machine-learning predictions, achieving over 95 % accuracy in forecasting pest life cycles. Smart traps equipped with high-resolution cameras automatically detect and identify pests. Additionally, predictive algorithms analyse environmental data to help farmers act quickly against threats. Accessible through a digital platform, xTrap empowers farmers to protect their crops effectively.

Objective

xTrap is an innovative smart trap solution that will transform pest management operations in farms, fostering the transition towards the Agriculture 4,0 era. It combines real-time automatic monitoring of pest insects with prediction based on machine-learning models. xTrap is the first predictive solution for pest life-cycle events (over 95% accuracy) on the market. It accurately identifies crop pests and diseases in time, therefore allowing farmers to prevent them effectively. xTrap includes two main functions: 1) automatic insect detection through smart traps equipped with sensors and high-resolution cameras to count and identify insects by means of machine-learning algorithms, and 2) pest prediction through algorithms based on environmental data and phenology of insects combined with the use of artificial intelligence. The output from the algorithms and the predictive models will be available to farmers through our digital platform currently being commercialized by xFarm.

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

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-EIC-ACC-BF - HORIZON EIC Accelerator Blended Finance

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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-EIC-2022-ACCELERATOR-01

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Coordinator

XFARM TECHNOLOGIES ITALIA SRL
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.

€ 870 625,00
Address
VIA LANZA 29
15040 Valmacca
Italy

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Nord-Ovest Piemonte Alessandria
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
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.

€ 1 243 750,00
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