Expanding Appliance for Image Identification Modules
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Solution Overview
Problem
Existing image identification systems are inflexible and inefficient when required to perform multiple image identification functions simultaneously, as they often necessitate hardware upgrades or result in reduced performance and increased costs due to fixed hardware specifications.
Innovation Solution
An expanding appliance that connects and manages multiple image identification function modules through an intelligent control module, allowing for real-time expansion of identification functions without affecting hardware performance, enabling simultaneous execution of multiple identification procedures and providing user-specific results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple image identification functions are executed simultaneously in a single system, then the system's identification capability is improved, but the hardware specification and computing resources required increase significantly
Solution Approach 1:
The system divides image identification functions into separate, independent function modules that can be individually selected and executed. Each module handles a specific identification task (e.g., face recognition, object detection), allowing the system to segment complex multi-function requirements into manageable, independent units that reduce overall hardware demands.
Solution Approach 2:
The system employs a universal execution platform that can run multiple different image identification function modules through a common interface and resource management layer. This multi-functional architecture allows a single hardware system to adaptively execute various identification functions without requiring dedicated hardware for each function type.
2Adaptability or versatility
If additional image identification functions are added to an existing system, then the system's functionality is improved, but the computation loading exceeds hardware capacity and reduces identification efficiency
Solution Approach 1:
The system implements dynamic function module selection and execution, where the execution platform adaptively loads, activates, or suspends specific function modules based on real-time computational capacity and identification efficiency requirements. This dynamic adjustment allows the system to maintain optimal performance while accommodating varying functional demands.
Solution Approach 2:
The system changes operational parameters such as computing resource allocation, processing priority, and module activation states to balance function expansion with identification efficiency. By dynamically adjusting these parameters, the system can add new identification functions without exceeding hardware capacity or compromising the efficiency of existing functions.
3Quantity of substance
If image identification functions are removed from a system, then the hardware cost is reduced, but the system's adaptability to client requirements decreases
Solution Approach 1:
The system extracts image identification functions into separate, removable function modules that can be selectively activated or deactivated. This extraction allows the system to remove unused identification functions from active execution, reducing hardware resource consumption and cost, while maintaining the capability to restore or add functions as client requirements change.
Data Source
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AI summary
An expanding appliance (1) including a connect port (13), an image capturing module (12), an intelligent control module (11), an image transmitting module (15), and a result displaying module (16) is disclosed, wherein the expanding appliance (1) connects an image input device (2) through the connect port (13), connects a display device (2) through the result displaying module (16), and connects one or more image-applied function module (3) through the image transmitting module (15). The intelligent control module (11) generates a demanding command according to a successfully-connected image-applied function module (3). The image capturing module (12) controls the image input device (2) to capture image data based on the demanding command, and quantizes samples of the image data as computation data. The image transmitting module (15) provides the computation data to the image-applied function module (3) for image identification and receives an identification result. Finally, the intelligent control module (11) triggers the result display module (16) for displaying the identification result on the display device (4).