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GithubSingTown's intelligent camera system, based on OpenMV, enables automatic identification of pest traces on plant leaves, stems, and other parts. Utilizing AI image recognition and machine vision technology, the system captures features such as insect bites, spots, or lesions, assisting farms or researchers in real-time monitoring of plant health conditions to achieve precise pest control and smart agricultural management.

In modern agriculture and plant protection, timely detection of pest traces is crucial for crop health and yield. Traditional manual inspections are time-consuming, labor-intensive, and difficult to achieve full coverage. SingTown Technology's AI smart camera solution, based on the OpenMV platform, utilises machine vision and image recognition technology to develop an embedded vision system capable of automatically detecting pest traces on plant leaves, stems, and other parts.
The system employs cameras to capture crop imagery and integrates AI algorithms to examine leaf texture, colour variations, and the morphology of holes or spots, detecting indications of pests or potential disease zones. Computer vision technology further extracts and quantifies attributes such as location, size, and distribution, furnishing farms with visual pest distribution maps and real-time notifications.
The OpenMV intelligent camera, with its compact size and low power consumption, can be flexibly deployed at the edge in greenhouses, field monitoring points, or drone platforms, enabling continuous all-weather monitoring. Users can train models based on different plant species, leaf morphologies, or pest types to enhance recognition accuracy and adaptability.
SingTown Technology integrates edge AI, machine vision, and image recognition technologies at a profound level, empowering smart cameras to "perceive" subtle traces of pests. This delivers precise, automated monitoring and control solutions for smart agriculture, thereby enhancing the efficiency of crop health management and overall productivity.

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