SingTown Technology employs AI vision to create a new tool for pest detection, offering precision, real-time capabilities, and high efficiency.

SingTown's intelligent camera system, based on OpenMV, enables automatic identification of pest traces on plant leaves, stems, and other parts. Utilising 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, labour-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 utilises cameras to capture crop images and combines AI algorithms to analyse leaf texture, colour variations, and the morphology of holes or spots, identifying traces of pests or potential disease areas. Computer vision technology further extracts and quantifies characteristics such as location, size, and distribution, providing farms with visual pest distribution maps and real-time alerts.

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 deeply integrates edge AI, machine vision, and image recognition technologies, enabling smart cameras to "see" subtle pest traces. This provides precise, automated monitoring and control solutions for smart agriculture, enhancing crop health management efficiency and productivity.