Dust, fallen leaves, or obstructions on the photovoltaic panels are automatically identified as hazards by OpenMV.

The fact that solar panels “appear to be fine” does not necessarily indicate normal power generation efficiency. Localized shading and dust accumulation often persist for extended periods yet remain difficult to detect. OpenMV enables photovoltaic operations and maintenance to move beyond full reliance on manual inspections.

During photovoltaic (PV) power station operation, foreign matter such as dust accumulation, leaf buildup, and bird droppings on PV panel surfaces directly reduces light absorption efficiency, leading to decreased power generation; over time, this may even accelerate component aging and shorten equipment service life.

For large-scale photovoltaic arrays, manual inspection is not only inefficient but also unable to promptly detect localized anomalies. Leveraging SingTown’s OpenMV intelligent cameras, long-term and stable visual monitoring of photovoltaic panel operational status can be achieved, enabling automatic identification and timely resolution of foreign object issues.

The camera can be securely mounted on a support structure to cover multiple photovoltaic module areas and continuously capture images of the photovoltaic panel surfaces. OpenMV performs edge-side region segmentation to delineate the effective operating areas of the photovoltaic panels and, by combining foreign-object feature recognition with status comparison analysis, automatically determines whether abnormal dust accumulation, leaf obstruction, or localized contamination is present.

By comparing the current image with a normal reference, the system identifies abnormal areas affecting power generation efficiency and outputs the identification results. These results can directly trigger on-device cleaning equipment, operations and maintenance systems, or alarm modules to enable immediate response upon detection, eliminating the need to upload large volumes of image data to the cloud.

Leveraging OpenMV’s edge computing capabilities and low-power design, this solution is particularly suitable for long-term deployment in large-scale, distributed photovoltaic scenarios.