Augmented Reality Inventory Tracking Using Multi-Feature Recognition
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Solution Overview
Problem
Existing inventory tracking systems for devices, such as RFID tags and camera-based systems, are costly, cumbersome, and prone to errors due to misidentification and manual data entry, failing to accurately manage device configurations and settings.
Innovation Solution
An augmented reality system that identifies devices using a combination of features like images, depth maps, and optical character recognition, correlating multiple data points to enhance accuracy, and presents device-specific settings as an overlay on a live camera image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If RFID tags or barcodes are used to track inventory devices, then device identification capability is improved, but system cost and implementation complexity increase
Solution Approach 1:
The patent extracts the identification function from physical tags (RFID, barcode) and implements it through camera-based visual recognition. The system captures images of devices and extracts identifying features directly from the device appearance, eliminating the need for separate tagging infrastructure and reducing system complexity while maintaining identification accuracy.
Solution Approach 2:
The patent creates a digital reference library of device images and configurations that serves as a template for identification. Instead of requiring physical tags on each device, the system uses copied visual references from the library to match against captured device images, enabling tag-free identification through pattern recognition.
2Loss of time
If manual data entry and paper records are used for inventory management, then system cost is reduced, but time consumption and error rate increase
Solution Approach 1:
The patent replaces manual mechanical processes (paper handling, manual data entry, physical file searching) with automated digital systems. The camera captures device images, software automatically extracts identifying features, queries the reference library, and retrieves configuration data electronically, eliminating manual intervention and significantly reducing time while improving accuracy through automated data extraction.
Solution Approach 2:
The system enables self-service inventory management where the device identification and configuration retrieval processes occur automatically without human intervention. The camera and software work together to autonomously identify devices, match them with reference records, and present configuration information, freeing users from manual inventory management tasks.
3Device complexity
If camera-based systems are used to identify devices, then implementation cost is reduced, but identification accuracy decreases due to false positives
Solution Approach 1:
The patent merges multiple identification approaches into a unified system: visual image recognition, optical character recognition (OCR) for text extraction, and database correlation. By combining these methods, the system cross-validates identification results through multiple independent features, significantly reducing false positives while maintaining implementation simplicity through integrated software processing.
Data Source
AI summary
The present disclosure describes systems and methods for augmented reality inventory tracking and analysis that identifies devices based on a combination of features, retrieves a configuration or other characteristics of the selected device and presents the configuration as a rendered overlay on a live image from the camera.