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GithubTraditional fruit and vegetable sorting relies on manual assessment of size and appearance, which is not only inefficient and prone to errors but also struggles to meet the demands of large-scale processing.
To achieve automated grading and quality inspection of fruits and vegetables, manufacturers of fruit and vegetable processing equipment utilize SingTown Technology's OpenMV intelligent camera AI image recognition technology. Through AI machine vision and machine vision algorithms, real-time identification and grading of fruit volume and surface quality are achieved, enhancing the accuracy of automated sorting and production efficiency.

The fruit and vegetable sorting system, based on SingTown Technology's OpenMV intelligent camera AI image recognition technology, has developed an embedded AI vision solution that integrates volume detection and quality identification.
The system installs an OpenMV intelligent camera above the conveyor belt to capture real-time images of fruits. Through edge-deployed computer vision algorithms, it analyzes the size, shape, and color characteristics of the fruits, automatically classifying them into large, medium, and small grades. Based on the results, it controls the sorting mechanism to convey fruits of different specifications to their corresponding collection bins.
Simultaneously, on-device AI can detect surface imperfections, blemishes, and signs of decay on fruits, enabling the automatic distinction between quality produce and substandard items.
SingTown OpenMV intelligent camera possesses edge computing capabilities, enabling it to run recognition models directly on-device without requiring external computational resources. With recognition latency under 30 milliseconds, it is suitable for high-speed sorting scenarios.
Through SingTown Technology's OpenMV intelligent camera AI image recognition technology, the fruit and vegetable sorting system has achieved an upgrade from manual screening to AI visual quality inspection and automatic sorting, significantly enhancing sorting efficiency and quality control stability.

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