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

The photovoltaic panel “appears to be fine” does not necessarily indicate normal power generation efficiency. Local shading and dust accumulation often persist for extended periods yet remain difficult to detect. OpenMV enables photovoltaic operation and maintenance to no longer rely entirely on manual inspections.

During the operation of photovoltaic power plants, foreign substances such as dust accumulation, fallen leaves, and bird droppings on the surface of photovoltaic panels directly reduce light absorption efficiency, resulting in decreased power generation; over the long term, these issues 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 (PV) module areas and continuously capture images of the PV panel surfaces. OpenMV performs edge-side regional segmentation to identify the effective operating areas of the PV panels, and automatically detects abnormal dust accumulation, leaf obstruction, or localized contamination by combining foreign object feature recognition with status comparison analysis.

By comparing the current image with a normal reference, the system identifies abnormal areas affecting power generation efficiency and outputs the detection results. These results can directly trigger on-device cleaning equipment, operation and maintenance systems, or alarm modules to enable immediate action 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.