logo
OpenMV
Home Cam
Applications
Store
AI
Sales Channels
Support
OpenMVOpenMV
ShieldsShields
LensLens
RoboticsRobotics
BookBook
VideoVideo
DownloadDownload
DocsDocs
ForumForum
OpenMV.ioOpenMV.io
GithubGithub

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

The fact that solar panels “appear 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.

光伏板异物识别

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, leading to decreased power generation; over time, these issues may even accelerate component aging and shorten equipment service life.

For large-scale photovoltaic arrays, relying on manual inspections is not only inefficient but also makes it difficult to promptly detect localized anomalies. Using SingTown’s OpenMV intelligent cameras enables long-term, stable visual monitoring of photovoltaic panel operational status, achieving automatic identification and timely handling 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 processing by using a region segmentation algorithm to delineate the effective operating areas of the photovoltaic panels, and automatically detects anomalies such as abnormal dust accumulation, leaf obstruction, or localized contamination through foreign object feature recognition and status comparison analysis.

By comparing the current image with the normal state, the system identifies abnormal areas affecting power generation efficiency and outputs the detection results. These results can directly trigger cleaning equipment, operation and maintenance systems, or alarm modules at the edge 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.

Related articles

机房/配电房/单元门敞开识别

AI Sentinel Based on OpenMV: Automatic Alert for Unlocked Key Locations

Automatically detects whether the door of a key location has remained open for an extended period and issues a timely alert.

越界识别

Personnel crossing the boundary triggers an alarm; OpenMV defines the “sense of security boundary.”

Detecting personnel or equipment crossing boundaries via virtual alert lines.

占道经营识别

“AI城管” is here: An automated system for detecting illegal street vending, built on OpenMV

Automatically identifies illegal street vending activities to support daily urban governance.

煤气罐违规摆放识别

Is the gas cylinder placed haphazardly? Use OpenMV to automatically trigger a hazard alert

Automatically identifies unauthorized placements of gas cylinders to detect potential gas safety hazards in advance.

绝缘手套佩戴识别

Did you perform live-line work without wearing insulating gloves? OpenMV will immediately alert you!

Automatically identifies whether workers are wearing insulating gloves to assist in safe operations.

铝板缺陷识别

Utilizing the OpenMV smart camera to detect surface defects on aluminum plates in real time

Online detection of surface defects on aluminum plates, such as scratches and dents, to support quality control.

Popular categories

Language and Region
Copyright © 2025 星瞳科技SingTown
粤ICP备17045162号