Dynamic Resource Linking via 3D Vehicle Overlay
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Solution Overview
Problem
Conventional tablet computing devices are limited in dynamically connecting users with relevant training resources and visually indicating areas of interest related to dynamically selected training content, especially when the user is in proximity to a vehicle, as they rely on static links and cannot identify or display resources based on the user's current location and interests.
Innovation Solution
A tablet computing device equipped with a processing circuit, camera, GPS receiver, and wireless transceiver that determines user-selected terms, generates a 3D coordinate system, and identifies areas of interest on a vehicle within the user's field of view, allowing dynamic connection to relevant resources based on user-defined prioritization and geographical location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional tablet computing devices use static links for training content navigation, then the device structure remains simple, but the adaptability to user interests and dynamic content connection is poor
Solution Approach 1:
The patent transforms the static link structure into a dynamic system where training resources are automatically connected based on user-selected terms. The processing circuit continuously monitors user interactions, dynamically generates attribute associations, and updates resource connections in real-time, allowing the system to adapt to changing user interests without manual reconfiguration.
Solution Approach 2:
The system changes the parameter of resource connection from fixed static links to dynamic attribute-based associations. By extracting attributes from user-selected terms and matching them with training resource metadata, the system creates flexible, context-aware connections that adapt to different user choices and training scenarios.
2Loss of information
If the tablet device implements dynamic resource identification based on user selection, then the relevance of training resources improves, but the processing complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing attribute schemas and resource metadata structures before user interaction. Training resources are pre-tagged with relevant attributes, and the processing circuit is pre-configured with association rules, enabling rapid dynamic matching without complex real-time analysis.
Solution Approach 2:
The patent introduces attributes as an intermediary layer between user-selected terms and training resources. Instead of directly matching complex content, the system extracts simple attributes from user selections and uses these as mediators to find relevant resources, simplifying the matching process while maintaining high relevance.
3Ease of operation
If the device visually indicates areas of interest on vehicles using 3D coordinate systems, then the user interaction quality improves, but the computational requirements increase
Solution Approach 1:
The system creates a virtual 3D coordinate system overlay that copies and maps onto the real-world vehicle view. Instead of manipulating complex 3D models directly, the processing circuit generates a simplified coordinate representation that mirrors the physical space, enabling intuitive user interaction with spatial relationships without heavy computational overhead.
Solution Approach 2:
The patent adds a visual dimension to training content by overlaying 3D coordinate indicators on the vehicle display. This dimensional enhancement allows users to interact with spatial information intuitively through visual cues like highlighted areas and coordinate markers, improving ease of operation without requiring complex haptic or physical interfaces.
4Adaptability or versatility
If the tablet computing device integrates multiple sensors and processing functions, then the functionality for dynamic resource connection improves, but the device complexity increases
Solution Approach 1:
The processing circuit is designed as a universal platform that handles multiple functions: capturing user selections, extracting attributes, querying training resources, generating 3D coordinate systems, and controlling display outputs. This multi-functional approach consolidates what could be separate specialized components into a single versatile processing unit, managing complexity while maintaining adaptability.
Data Source
AI summary
A tablet computing device displays training content to a user. Upon detecting the user-selection of a term in the content, the tablet computing device identifies one or more categories that are associated with the selected term and obtains additional training resources related to the user-selected term based on those categories. Additionally, the tablet computing device captures the image of a vehicle, such as an aircraft, within its field of view for display to the user. Given the image, the tablet computing device identifies areas on the vehicle that may be related to the user-selected term and generates touch controls for those areas. The user can touch those controls to retrieve the additional training resources.