Augmented Reality Detection for Data Center Enterprise Systems
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Solution Overview
Problem
Managing and tracking thousands of information handling systems in a data center environment is challenging due to the difficulty in detecting, classifying, and locating hardware effectively.
Innovation Solution
An augmented reality system that captures views of enterprise systems, detects significant areas, adds bounding boxes, determines three-dimensional orientation, and calculates depth using camera images, RSSI measurements, and accelerometer data to provide accurate object detection and localization within the data center.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual tracking methods are used for information handling systems, then implementation simplicity is maintained, but detection precision and location accuracy deteriorate
Solution Approach 1:
The patent replaces manual tracking methods with an automated augmented reality system that uses camera imaging, RSSI measurements, and accelerometer data to automatically detect and locate information handling systems. This substitution of mechanical/manual operations with automated sensing and processing systems directly resolves the contradiction by improving detection precision while managing system complexity through integrated automation.
Solution Approach 2:
The patent introduces an augmented reality application as an intermediary layer between the physical data center environment and the management system. This intermediary captures images, processes RSSI signals, and presents location information through AR interfaces, thereby improving detection precision while abstracting the complexity of the underlying sensing and processing systems.
2Loss of information
If comprehensive tracking of all hardware is implemented, then information completeness is improved, but ease of operation deteriorates
Solution Approach 1:
The augmented reality system enables operators to perform self-directed detection and tracking by simply pointing a device at the data center environment. The system automatically captures images, processes sensor data, and presents location information without requiring complex manual procedures, thereby maintaining information completeness while improving ease of operation through intuitive AR interfaces.
Solution Approach 2:
The patent adds a spatial dimension to information presentation by overlaying location data, bounding boxes, and depth information directly onto the visual field through augmented reality. This dimensional transformation allows comprehensive hardware tracking information to be presented intuitively in three-dimensional space, improving ease of operation while maintaining complete information about all tracked systems.
3Measurement precision
If detailed detection of significant areas is performed, then detection precision is improved, but processing time increases
Solution Approach 1:
The patent segments the detection process by identifying and focusing on significant areas within the captured images rather than processing entire images uniformly. By detecting bounding boxes around specific hardware components and calculating their three-dimensional orientations selectively, the system improves detection precision for critical elements while reducing overall processing time through targeted analysis.
Solution Approach 2:
The system performs partial detection by focusing computational resources on identifying and measuring significant areas and objects rather than analyzing every pixel or detail equally. This selective processing approach maintains sufficient detection precision for location and orientation while reducing processing time by avoiding excessive analysis of non-critical regions.
Data Source
AI summary
A system, method, and computer-readable medium are disclosed for augmented reality detection of enterprise systems in a data center. An augmented reality view is captured of an enterprise system and objects of the enterprise system. Significant areas are detected of the enterprise. In the captured augmented reality view bounding boxes are added around the significant areas. Determination is performed of three-dimensional orientation of the significant areas. Depth of the signification areas is determined based on the three-dimensional orientation.