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

At live electrical work sites, a single moment of negligence can lead to serious consequences. Relying solely on safety personnel for inspections makes it extremely difficult to ensure continuous monitoring throughout the entire process. OpenMV enables the system to perform real-time verification of 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, continuous, and standardized control.

Based on SingTown Technology’s OpenMV smart camera, the system can automatically and in real time identify whether workers are wearing their 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 workers are wearing insulating gloves and identify cases of non-wearing or improper wearing.

When a violation is detected, OpenMV can instantly output an alert signal at the edge, triggering on-site audio-visual alarms, voice prompts, or operational systems to enable immediate intervention and prevent hazardous operations from continuing.

Since identification and judgment are fully 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 caused by human error.