SingTown Technology's visual AI empowers agricultural equipment to achieve automated plastic film detection.

In the process of agricultural mechanized planting, the quality of plastic film laying directly affects heat preservation, moisture retention, and crop emergence rates.
Traditional manual inspection methods are inefficient, prone to errors, and incapable of detecting film damage or misalignment in real time during operations.
To address this issue, agricultural equipment manufacturers have adopted SingTown's OpenMV intelligent camera recognition technology, integrating AI machine vision and image recognition algorithms to achieve detection of mulch film width and identification of damage.
The system can monitor the film laying status in real-time under complex field conditions (including dust, smoke, glare, etc.), promptly detect anomalies, and is widely applied in agricultural equipment fields such as plastic film laying machines, seeders, and automatic film laying machines.

Agricultural equipment manufacturers utilize SingTown's OpenMV intelligent camera recognition technology to achieve real-time monitoring and quality warning of plastic film laying status.

The solution involves installing an industrial-grade camera at the rear of the equipment, with its field of view directed toward the ground behind. Its embedded vision system and edge-side AI can be used to detect the laying status of plastic film, approximately 2.05 meters wide, in real time. By employing edge detection, shape recognition, and regional brightness analysis algorithms, the boundary lines of the film are extracted, and the film laying width is calculated in real time.

Meanwhile, the AI algorithm determines whether the film has cracks, holes, or wrinkles through texture continuity analysis and brightness mutation detection.

When the film is damaged, has uneven width, or is blown by wind, the OpenMV module immediately outputs an alarm signal or transmits the detection results via serial port to the vehicle control system, enabling real-time alerts or automatic shutdown.

The system don dey fine-tune for image preprocessing for inside field environments wey get strong light, dust, and glare, to make sure say e dey recognize things well-well and e fit continue to detect even for inside complex situations like when e dey run fast (5–10 km/h). The whole recognition process no dey pass one second.

Through the computer vision and image recognition technology of SingTown's machine vision intelligent cameras, agricultural equipment manufacturers have achieved real-time monitoring and anomaly feedback for the quality of plastic film laying, effectively enhancing the automation and intelligence level of agricultural machinery operations.