OpenMV
Shields
Lens
Robotics
Book
Video
Download
Docs
Forum
OpenMV.io
GithubAt live-working 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-event inspections, making it difficult to achieve comprehensive, continuous, and standardised control.
Based on SingTown’s OpenMV intelligent camera, the system can automatically and in real time identify whether personnel are wearing their personal protective equipment, thereby 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 wear-status recognition model, the system can accurately determine whether personnel are wearing insulating gloves and identify instances of non-wear or improper wear.
When violations are detected, OpenMV can instantly output an alert signal on-device to trigger on-site audible and visual alarms, voice prompts, or operational systems, enabling immediate intervention and preventing hazardous operations from continuing.
As all identification and decision-making are completed 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. Through OpenMV’s edge AI vision capabilities, safety protection has shifted from “relying on experience and manual effort” to “relying on data and systems”, significantly reducing safety risks arising from human error.

AI Sentinel Based on OpenMV: Automatic Alert for Unsecured Key Locations
Automatically detects whether the door of a key location has remained open for an extended period and issues a timely alert.

Personnel crossing the boundary triggers an alarm; OpenMV interprets the “sense of security boundary”
Detects personnel or equipment crossing virtual perimeter lines.

“AI Municipal Enforcement” is here: an automated unauthorised trading detection system built on OpenMV
Automatically identifies illegal street vending activities to support daily urban governance.

Improper storage of gas cylinders? Use OpenMV to automatically trigger hazard alerts
Automatically identifies non-compliant placement of gas cylinders to proactively detect gas-related safety hazards.

Did you perform live-line work without wearing insulating gloves? OpenMV will immediately issue an alert!
Automatically identifies whether personnel are wearing insulating gloves to assist with safe operations.

Utilise the OpenMV smart camera to identify surface defects on aluminium plates in real time
Online identification of defects such as scratches and dents on aluminium plate surfaces to support quality control.