AR-Based Diagnostic System for Field Technicians
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Solution Overview
Problem
Field technicians face challenges in diagnosing and troubleshooting computing systems without access to management networks, as their devices may be malfunctioning or they lack authorization, limiting their ability to remotely assess system status and provide effective solutions.
Innovation Solution
A system comprising a capture device, memory with a management module, and a processor that captures environmental inputs, identifies target devices, compares them to models, and provides real-time status recognition and troubleshooting data, enabling remote diagnostics and error resolution without network access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If field technicians access management network to diagnose computing systems, then they can obtain error logs and system status information, but their diagnostic capability is limited when management network is inaccessible or when they lack authorization
Solution Approach 1:
The patent introduces an intermediary device positioned between the computing system and the field technician's mobile device. This intermediary captures images of the computing system, processes them locally to extract diagnostic information, and transmits only the extracted data to the mobile device. This mediator enables diagnostic capability to function independently of management network access, resolving the contradiction by providing an alternative information pathway that does not require network connectivity or special authorization.
Solution Approach 2:
The system extracts only the necessary diagnostic information from images of the computing system using image processing algorithms. Instead of requiring full access to the management network or system files, the intermediary device extracts relevant status indicators, error codes, and system parameters directly from visual data. This extraction approach provides sufficient diagnostic capability while eliminating the need for management network access or authorization.
2Adaptability or versatility
If field technicians manually inspect computing systems without network access, then they can operate independently, but the time required for diagnosis and troubleshooting increases significantly
Solution Approach 1:
The intermediary device performs preliminary image capture and processing actions before the field technician arrives or while they are en route. The system pre-extracts diagnostic information from images of the computing system, preparing troubleshooting data in advance. When the technician arrives, the diagnostic information is already processed and ready for immediate review on their mobile device, significantly reducing on-site diagnosis time while maintaining independent operation capability.
Solution Approach 2:
The patent replaces manual mechanical inspection methods with automated optical imaging and computer vision algorithms. Instead of physically examining components, connecting to systems, or manually reading indicators, the intermediary device uses image capture and automated processing to extract diagnostic information. This substitution eliminates time-consuming manual inspection steps while enabling independent operation, directly addressing the time loss problem.
3Measurement precision
If comprehensive troubleshooting data is provided to field technicians, then diagnostic accuracy improves, but data transmission and processing requirements increase
Solution Approach 1:
The intermediary device extracts only the essential diagnostic information from images of the computing system, isolating critical error codes, status indicators, and system parameters from the full visual data set. This selective extraction provides sufficient diagnostic accuracy for field technicians while transmitting minimal data volumes over the network, resolving the contradiction between comprehensive data provision and data quantity constraints.
Solution Approach 2:
The system applies different processing quality levels to different parts of the image data. Critical diagnostic regions (such as display screens showing error codes or status LEDs) are processed with high precision to ensure accurate data extraction, while non-critical areas are processed with lower detail. This local quality approach maintains diagnostic accuracy for essential information while reducing overall data transmission requirements.
Data Source
AI summary
Systems and methods for managing computing systems are provided. One system includes a capture device for capturing environmental inputs, memory storing code comprising a management module, and a processor. The processor, when executing the code comprising the management module, is configured to perform the method below. One method includes identifying a target device in a captured environmental input, and comparing the target device in the captured environmental input to a model of the target device. The method further includes recognizing, in real-time, a status condition of the target device based on the comparison and providing a user with troubleshooting data if the status condition is an error condition. Also provided are physical computer storage mediums including a computer program product for performing the above method.