Did you perform live-line work without wearing insulating gloves? OpenMV issues an immediate alert!

At live-line work sites, a single moment of negligence can lead to severe consequences. Relying solely on safety personnel for on-site inspections makes it difficult to ensure continuous monitoring throughout the entire process. OpenMV enables the system to perform real-time judgment on whether gloves are being worn.

Correctly wearing insulating gloves during power maintenance, live-line work, and equipment maintenance is a critical prerequisite for ensuring personnel safety. However, in actual operational scenarios, traditional supervision methods largely rely on on-site monitoring by safety officers or post-event inspections, making it difficult to achieve comprehensive, continuous, and standardized control.

Based on SingTown’s OpenMV smart camera, the system can automatically and in real time identify whether personnel are wearing protective equipment, upgrading safety inspections from “manual monitoring” to “system-based perception.”

The camera can be deployed above the work area or at critical operation points. OpenMV continuously captures operational footage at the edge, locates personnel through a human detection algorithm, and further performs fine-grained detection and tracking of hand regions.

By integrating color features, shape contours, and a wear-status recognition model, the system can accurately determine whether personnel are wearing insulating gloves and identify cases of non-wear or improper wear.

When violations are detected, OpenMV can instantly output an alert signal on the edge side to trigger on-site audio-visual alarms, voice prompts, or operational systems, enabling immediate intervention and preventing hazardous operations from continuing.

Since all recognition and judgment are performed on the camera’s edge side, the system does not rely on cloud computing, enabling fast response times and stable deployment—making it especially suitable for environments with extremely high requirements for real-time performance and reliability, such as power field operations. Leveraging OpenMV’s edge-side AI vision capabilities, safety protection shifts from “relying on experience and manual labor” to “relying on data and systems,” significantly reducing safety risks arising from human error.