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

A photovoltaic panel that “appears to be functioning normally” does not necessarily indicate normal power generation efficiency. Localised 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 the long term, this may even accelerate component ageing and shorten equipment service life.

For large-scale photovoltaic arrays, manual inspection is not only inefficient but also unable to promptly detect local anomalies. Using SingTown’s OpenMV intelligent cameras enables long-term, stable visual monitoring of photovoltaic panel operational status, facilitating 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 PV panel surfaces. OpenMV performs edge-side regional segmentation to delineate the effective operating areas of the PV panels, and automatically detects abnormal dust accumulation, leaf obstruction, or local contamination by combining foreign-object feature recognition with status comparison analysis.

By comparing the current image with a normal state, the system identifies abnormal areas affecting power generation efficiency and outputs the identification results. These results can directly trigger cleaning equipment, operations and maintenance systems, or alarm modules on the device side, enabling immediate action upon detection without uploading 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.