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

At live electrical work sites, a single moment of negligence can lead to serious consequences. Relying solely on safety officers for inspections makes it difficult to ensure continuous monitoring throughout the entire process. OpenMV enables the system to determine in real time 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-incident inspections, making it difficult to achieve comprehensive, continuous, and standardised control throughout the entire process.

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

Cameras can be deployed above work areas or at critical operational points. OpenMV continuously captures operational footage at the edge, locates personnel through human detection algorithms, and further performs fine-grained detection and tracking of hand regions.

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

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

As all identification 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 sites. 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 arising from human error.