Robcam: the smart, automatic AI pest detector
Added on 05 June 2025

Daily detection with exceptional precision
Pests like thrips and whitefly can cause major damage to crops, making early detection critical. While crop specialists typically scout manually and weekly, Robcam does so automatically and every day. Equipped with a microscope camera (25,000 pixels per mm²) and powerful LED lighting, Robcam performs a daily scan of 150 high-resolution images. Artificial intelligence automatically identifies and counts pests and beneficial insects, including thrips, whitefly, aphids, leaf miners, and diglyphus.
Less labor, greater impact
Robcam provides growers with a reliable, digital overview of pest pressure in their crops—enabling faster and more targeted interventions with less manual work. The data is clearly displayed in the Auxin dashboard, where it can be easily compared with information from other digital tools connected to Auxin. The smart detector is suitable for both vegetable and ornamental growers. Robcam runs on battery or mains power and can be easily mounted anywhere in the greenhouse where Wi-Fi is available. The traps, coated with Royal Brinkman’s adhesive, are simple to replace for maximum effectiveness.
Combining forces for smarter crop protection
The collaboration between Royal Brinkman and Robtelli combines innovative technology with deep horticultural knowledge. “Robcam aligns seamlessly with Royal Brinkman’s Integrated Crop Management (ICM) approach,” says Gert-Jan van Heusden, Innovation Specialist at Royal Brinkman. “This smart trap scanner detects pests and beneficial insects at an early stage, enabling growers to act sooner and more precisely—matching the preventative nature of ICM.” Thanks to its high resolution and AI-powered recognition, Robcam delivers highly accurate and consistent data, enhancing the reliability of pest monitoring and offering an objective foundation for crop strategy decisions. By uniting expertise and technology, Robcam empowers growers to take a significant step forward in labor efficiency and data-driven crop protection.
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