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GithubTraditional fruit and vegetable sorting relies on manual judgment 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, fruit and vegetable processing equipment manufacturers utilise 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 fruit images. 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, edge AI can also detect surface defects, spots, decay, and other characteristics of fruits, enabling automatic differentiation between good-quality and substandard products.
SingTown Technology's OpenMV smart camera possesses edge computing capabilities, enabling it to run recognition models directly on-device without requiring external computational resources. With a recognition latency of less than 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 improving sorting efficiency and quality control stability.

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