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GithubModern agriculture is accelerating its transformation towards intelligence and automation. Traditional manual harvesting methods are inefficient, costly, and difficult to standardise. Particularly in orchard and field settings where fruit and vegetable ripeness is uneven and lighting conditions are complex, mechanical equipment struggles to accurately identify harvesting targets.
To address this challenge, agricultural equipment enterprises have introduced SingTown Technology's OpenMV intelligent camera AI image recognition technology. By leveraging machine vision, AI image recognition, and edge-side AI algorithms, they have developed an efficient and precise intelligent orchard harvesting system, enabling automatic identification, positioning, and accurate picking.

Agricultural equipment enterprises have adopted SingTown Technology's OpenMV intelligent cameras, deploying visual perception modules based on AI machine vision recognition algorithms on harvesting robots, achieving automatic detection and harvesting control of fruits and vegetables.
The system utilises high-performance cameras to capture real-time images of fruits and vegetables in the field. Through image recognition algorithms, it performs target identification, colour segmentation, and morphological analysis to accurately determine fruit ripeness and optimal harvesting timing.
By integrating deep learning models to classify the surface characteristics of fruit, the system can stably identify the location of mature fruit under varying lighting conditions, complex backgrounds, and fruit occlusion.
Upon completion of identification, the system utilises spatial coordinate calculations and robotic arm control algorithms to achieve three-dimensional positioning and precise grasping of the target fruit.
SingTown Technology's OpenMV smart camera possesses embedded edge computing capabilities. Its on-device AI can perform recognition and computation directly at the field equipment end, eliminating reliance on cloud networks and ensuring real-time performance and stability. Its automatic exposure and white balance functions can adapt to changes in lighting, sunlight, shadows, and reflective environments, guaranteeing recognition accuracy and image quality.
Leveraging SingTown Technology's integrated software and hardware platform, agricultural equipment enterprises can swiftly integrate the visual module of this embedded AI machine vision system into various models of harvesting robots, enabling automated recognition, precise picking, and yield data statistics.
Through SingTown Technology's OpenMV intelligent camera and smart image recognition technology, agricultural machinery has truly gained the ability to "see, understand fruit, and pick," driving agricultural production from manual picking experience towards AI vision-driven smart field operations.

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