1) Using infrared light sources to illuminate fruits;

2) Receive transmitted light carrying information about the fruit for analysis;

3) By establishing a model of fruit information, the system conducts deep learning on the model data to improve the accuracy of sorting;

4) It can be used to detect internal physiological indicators such as sugar content and mold heart disease.

1) Adopting omnidirectional diffuse reflection LED for uniform illumination, with no dead corners; 5 million pixel industrial camera with a resolution of 0.1 square millimeters;

2) Using multiple technologies such as CMOS image processing and pattern recognition, and using high-performance Advantech industrial control computers for image data processing;

3) It can accurately sort the surface color and shape of fruits.

1) By using imported high-speed and high-precision sensors, individual sensors, and specially designed fruit cups, fast and accurate weight readings are ensured, avoiding measurement errors;

2) Unique dynamic calibration and temperature compensation functions to avoid measurement errors caused by environmental differences;

3) Using three-dimensional visual imaging technology for all-round data collection, combining external quality characteristics and quality information to obtain density information, it can be used to detect fruits with drying and dehydration phenomena.

1) The individual fruits are placed in flexible fruit cups for transportation and testing, avoiding scratches and bumps during the sorting process;

2) Suitable for easily damaged fruits such as pears, peaches, apples, etc.