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)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- agricultural sciencesagriculture, forestry, and fisheriesagriculture
- natural sciencesbiological scienceszoologyentomology
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Programme(s)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Funding Scheme
HORIZON-EIC-ACC-BF - HORIZON EIC Accelerator Blended FinanceCoordinator
15040 Valmacca
Italy
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.