Depth Camera Operator Tracking for Manufacturing Safety
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Solution Overview
Problem
Large-scale manufacturing lines are difficult to monitor effectively without continuous in-person monitoring, leading to inefficiencies and safety hazards due to the tediousness of manual observation and data analysis.
Innovation Solution
A monitoring system that uses depth cameras to track operator movements in 3D space and receive operational status data, issuing commands to cease manufacturing line operations or alert systems when an operator is near a hazard, thereby enhancing safety and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous in-person monitoring and closed circuit video monitoring systems are used, then safety and quality monitoring capability is improved, but device complexity and operational burden increase significantly
Solution Approach 1:
The patent replaces manual in-person monitoring and human-operated video monitoring systems with an automated computer vision system using depth cameras and skeleton tracking algorithms. This substitutes mechanical/human observation with an automated optical-digital system that continuously monitors operator positions and movements without requiring human operators to watch screens or take notes.
Solution Approach 2:
The monitoring system performs self-service by automatically capturing depth images, generating skeleton models, tracking movements, detecting hazards, and issuing alerts without requiring continuous human intervention. The system serves itself by autonomously completing the entire monitoring workflow from data collection to safety decision-making.
2Loss of information
If manual observation and data analysis are used to study worker movements, then detailed movement data can be collected, but time consumption and labor requirements increase significantly
Solution Approach 1:
The patent replaces manual observation and data entry processes with automated depth camera capture and skeleton tracking technology. The system automatically captures three-dimensional movement data, generates skeletal representations of operators, and tracks movements through algorithms without requiring manual note-taking or data transcription, thereby preserving complete movement information while eliminating time-consuming manual processes.
Solution Approach 2:
The system creates digital copies of physical movements through skeleton models that replicate operator positions, orientations, and movements in virtual space. These skeleton copies allow for automated analysis and comparison of movement patterns without requiring physical observation or manual recording of actual movements.
3Reliability
If random in-person audits are conducted, then safety issues can be detected, but monitoring coverage and consistency are insufficient
Solution Approach 1:
The patent implements continuous monitoring by capturing depth images at regular intervals (e.g., every second) and continuously tracking operator movements through skeleton analysis. This ensures uninterrupted observation of the workstation region, maintaining constant safety surveillance without the gaps inherent in periodic audits, thereby improving both reliability of detection and overall monitoring efficiency.
Data Source
AI summary
Systems and method for monitoring a workstation region of a manufacturing line are provided. In one example, depth image data is received from one or more depth cameras trained on the workstation region, with the data comprising a temporal sequence of images of an operator. Using the depth image data, a series of movements of the operator is tracked in 3D space of the workstation region. Operational status data is received from the manufacturing line indicating the manufacturing line is operating. Using the series of movements, the operator is determined to be within a predetermined distance of a hazard. In response, a command is issued to the manufacturing line to cease operating.