Performing live-line work without wearing insulating gloves? OpenMV issues an immediate alert!

At live-line working sites, a single moment of negligence can lead to severe consequences. Relying solely on safety personnel for inspections makes it difficult to achieve continuous, real-time monitoring. OpenMV enables the system to determine in real time whether gloves are being worn.

In power maintenance, live-line work, and equipment maintenance, the correct wearing of insulating gloves 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 and continuous compliance control.

Based on SingTown’s OpenMV intelligent camera, the system can automatically and in real time identify whether workers 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 wearing-status recognition model, the system can accurately determine whether personnel are wearing insulating gloves and identify cases of non-wearing or improper wearing.

When violations are detected, OpenMV can instantly output alarm signals 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 identification and judgment are completed on the camera’s edge side, the system does not rely on cloud computing, ensuring 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 effort” to “relying on data and systems,” significantly reducing safety risks caused by human oversight.