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Demonstrates improved pest surveillance efficiency in greenhouse and outdoor settings, suggesting enhanced grower accessibility.
Pest monitoring in agriculture is essential but often slow, error-prone, and physically demanding. We propose two automated solutions tailored to different cultivation contexts. For controlled indoor/greenhouse environments, we deploy LED traps with cameras that capture images for an automated recognition pipeline to count and classify insects. For outdoor settings and large indoor settings, where the aforementioned solution is not feasible, a mobile app records leaf images with QR-linked metadata and uploads them for server-side image analysis. Both systems provide aggregated counts, species identification, and easy sharing of results, improving the efficiency, accuracy, and accessibility of pest surveillance for growers.
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Becker et al. (2026) studied this question.
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