Vendor-Agnostic Inference Appliance for Unified Screening AI
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Solution Overview
Problem
Existing screening technologies in high-throughput, secure environments suffer from duplication of computational resources, obsolescent infrastructure, lack of interconnection between elements, slower screening, increased labor requirements, and reduced detection efficiency due to the use of multiple vendor-specific devices with disparate software and hardware.
Innovation Solution
A vendor-agnostic interconnection system that integrates multiple vendor software packages, providing a unified dataset and image format for analysis, using a high-performance appliance with GPU-based AI inferencing and failover capabilities, allowing rapid updates and integration of new technologies without re-certification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple vendor-specific screening devices and software packages are used in parallel, then diverse screening capabilities are achieved, but device complexity and lack of interconnection increase
Solution Approach 1:
The patent introduces a central server as an intermediary component that receives data from multiple vendor-specific screening devices and processes them through a unified AI algorithm. This mediator enables interconnection between disparate devices without requiring direct integration between them, reducing system complexity while maintaining versatility.
Solution Approach 2:
The system employs a universal AI algorithm hosted on a central server that can process data from various types of screening devices regardless of vendor. This multi-functional approach allows a single algorithm to handle diverse screening data formats and protocols, eliminating the need for vendor-specific processing for each device type.
2Adaptability or versatility
If stand-alone screening devices from multiple vendors are deployed, then screening coverage is comprehensive, but productivity and screening speed decrease
Solution Approach 1:
The patent merges the computational resources of multiple stand-alone devices by consolidating AI processing on a central server. This combination allows parallel processing of data from multiple devices simultaneously, increasing overall screening throughput and speed while maintaining comprehensive coverage through the integration of various device types.
3Reliability
If vendor-specific software packages are used for each screening device, then device functionality is optimized, but adaptability to new technologies and threats is reduced
Solution Approach 1:
The patent extracts the AI algorithm from the vendor-specific device software and hosts it independently on a central server. This separation allows the core algorithm to be updated, modified, or replaced without affecting the underlying screening devices. New algorithms can be deployed to address emerging threats while maintaining reliable device operation through the stable data collection and transmission infrastructure.
4Reliability
If computational resources are duplicated across multiple devices, then device independence is maintained, but loss of time and computational efficiency worsen
Solution Approach 1:
Instead of duplicating full computational resources on each device, the system creates a copy of the AI algorithm on a central server that serves all devices. This centralized copy eliminates redundant computational resources while maintaining the functional independence of each screening device, as each can still operate autonomously for data collection and transmission while sharing the common AI processing capability.
Data Source
AI summary
Urgent screening in high-throughput, secure environments such as emergency rooms, or security, typically involves multiple devices. Devices that are used for screening are diverse, and typically sourced from multiple vendors. Currently, devices are typically stand-alone. Further, large devices, are costly, having high capital expenses with long commercial lifetimes, sometimes approaching a decade or more. The result of these features leads to duplication of computational resources, obsolescent computational infrastructure, and lack of interconnection between elements. Aspects of this invention include a device, system, and methods to provide vendor-agnostic interconnection between the multiple elements of a defined environment. The disclosed approach untethers AI algorithms from data generation system and increases flexibility in deployment of newer technologies and algorithms. Example systems can be updated or replaced with new hardware, as computational capabilities develop on short or emergent quality improvement cycles, and can adapt nimbly to changes in threats, regulatory requirements or market developments.