Cable Connection Guidance Using Computer Vision Identification
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Solution Overview
Problem
In data centers, the increasing complexity and size lead to challenging and time-consuming cable connection installations due to the difficulty in identifying and properly routing various types of cables with similar connectors, often resulting in inefficiencies and potential system failures.
Innovation Solution
A system that uses cameras and computer vision to identify cable types and guide operators to correct installation locations through visual indicators and overlays, ensuring proper cable connections by matching cable ends with corresponding receptacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual cable installation methods are used in large data centers, then installation complexity increases and time consumption increases, but automation and guidance systems can reduce these issues
Solution Approach 1:
The system enables self-service by allowing the installation system to automatically identify cables, determine their correct destinations, and provide guidance without human intervention in the identification process. The cable installation guidance device autonomously processes cable information, generates routing paths, and displays instructions to operators.
Solution Approach 2:
The patent replaces manual mechanical cable identification and routing methods with an automated computer vision system using cameras and image processing. Instead of physically examining and manually determining cable routes, the system uses optical detection and digital image analysis to automatically identify cables and their destinations.
2Measurement precision
If visual identification methods are used for cables with similar connectors, then identification accuracy improves, but time consumption increases
Solution Approach 1:
The system maintains continuous useful action by processing cable identification and routing determination simultaneously rather than sequentially. As cables are fed through the installation device, the camera system continuously captures images, the processing unit continuously analyzes them to identify cable types and destinations, and the guidance system continuously provides feedback, eliminating idle time between identification steps.
Solution Approach 2:
The system creates digital copies of cable visual information through camera imaging and stores routing information in digital form. Instead of requiring operators to physically examine and remember cable characteristics, the system captures visual copies via cameras and processes them through image recognition algorithms, enabling rapid and accurate identification without manual inspection time.
3Reliability
If automated cable routing systems are implemented, then installation error rate decreases, but system complexity increases
Solution Approach 1:
The system implements feedback by continuously monitoring cable identification results and comparing them against the routing database, then providing real-time guidance feedback to operators through displays or automated mechanisms. The system adjusts its guidance based on actual cable properties detected, ensuring accurate routing decisions and enabling error correction before installation is completed.
Data Source
AI summary
Configurations for rack connection systems are disclosed. In at least one embodiment, installation locations for one or more cables are determined and one or more indicators corresponding to installation locations are activated.