Image-based automated ergonomic risk root cause and solution identification system and method
An image-based deep learning system identifies ergonomic risks and solutions in industrial settings, addressing the scarcity of experts and preventing WMSDs through automated analysis.
AU2024399486A1Pending Publication Date: 2026-07-23VELOCITYEHS HOLDINGS INC
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Patent Information
- Application Number
- AU2024399486
- Authority / Receiving Office
- AU · AU
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-12-11
- Filing Date
- 2024-12-11
- Publication Date
- 2026-07-23
AI Technical Summary
Technical Problem
Existing methods struggle to automatically identify ergonomic risks and their solutions in industrial settings due to the scarcity of ergonomic experts, leading to challenges in preventing work-related musculoskeletal disorders (WMSDs) and significant economic burdens.
Method used
An image-based system utilizing deep learning techniques, including vision transformers and natural language processing, to analyze worker images and generate captions identifying ergonomic risks and corresponding solutions.
Benefits of technology
Enables efficient and cost-effective identification of ergonomic risks and solutions without relying on expert intervention, reducing WMSDs and associated healthcare costs.
✦ Generated by Eureka AI based on patent content.
Abstract
Disclosed herein is an image-based system configured to identify root causes of industrial ergonomic risks and their corresponding solutions. An example system comprises a computing device configured to encode an image of a worker performing a work task to generate an embedding vector, transmit the embedding vector to an image-grounded text decoder, while generating first tokens to instruct the decoder to generate a first sentence indicating a root cause of an ergonomic risk identified in the image, compute first relative sensitivity scores relating to the first tokens and extracted image features, generate second tokens of the first sentence based on the first relative sensitivity scores, while generating third tokens to instruct a text decoder to generate a second sentence indicating a solution to the ergonomic risk, calculate second relative sensitivity scores relating to the second and third tokens, and generate the first and second sentences accordingly.
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