Wearable Action Prediction With AR Warnings for Asset Workflows
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Solution Overview
Problem
Contemporary device ecosystems do not integrate multiple contextual situations, leading to inefficient workflows due to changes in machine installations, removals, or user influences, affecting safety and security.
Innovation Solution
A system comprising wearable computing devices that detect user movements and predict impending actions, generating warnings through augmented reality glasses about potential consequences before the actions are taken.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wearable devices detect user movements and predict predetermined actions, then safety is improved by warning users of potential consequences, but device complexity increases due to multiple sensors and processing requirements
Solution Approach 1:
The system divides the wearable equipment into multiple functional components: first wearable computing device for movement detection, second wearable computing device for prediction and warning, and augmented reality glass for display. This segmentation allows each component to specialize in specific tasks, improving overall safety functionality while distributing complexity across separate units.
Solution Approach 2:
The system performs preliminary action by predicting predetermined actions before the user actually performs them. The second wearable computing device analyzes detected movements in advance and generates warnings about potential consequences before the harmful action occurs, enabling preventive safety intervention.
2Productivity
If the system integrates multiple contextual situations including machine installations, removals, and user influences, then workflow efficiency is improved, but device complexity and processing requirements increase
Solution Approach 1:
The wearable computing devices serve multiple functions: detecting user movements, receiving machine status information, predicting actions, generating warnings, and integrating various contextual situations. This multi-functionality allows a single device to handle diverse workflow scenarios including machine installations, removals, and user influences, improving workflow efficiency without requiring separate specialized systems for each function.
Solution Approach 2:
The wearable computing devices act as intermediaries between machines and users, integrating information from multiple sources including machine status, user movements, and contextual situations. This intermediary role allows the system to process and synthesize diverse information streams, improving workflow efficiency by providing a unified view of the operational context.
Data Source
AI summary
Methods for intelligent management of asset workflows are disclosed herein. One method includes predicting that a user is going to perform a predetermined action based on one or more user movements included in a signal received from a wearable sensing device and generating, by a processor, a warning of one or more consequences of the user performing the predetermined action. The method further includes displaying, on augmented reality glass, the warning to the user prior to the user actually performing the predetermined action. Also disclosed herein are systems and apparatus that can include, perform, and/or implement the operations of the methods.