Mobile-Centric AI Agent Hub for Secure Cross-Device Synchronization
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Solution Overview
Problem
The challenge lies in synchronizing user-customized AI models across various devices in a safe and reliable manner, ensuring consistent and continuous user services, particularly when AI models are used in different user terminals such as personal computers, smart cars, and IoT devices, and maintaining information consistency and continuity between these environments.
Innovation Solution
A mobile-centric agent hub system (MCAHS) is introduced, which includes a safe execution environment and operating method, utilizing a computer device with a processor to register, authenticate, and select AI agents based on user instructions, integrating their results to provide a final response, while managing resource use and access rights through a trusted AI agent operation environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If AI models are synchronized across various user terminals (PC, laptop, tablet, smart car, IoT device), then service consistency and continuity are improved, but information security and reliability during synchronization deteriorate
Solution Approach 1:
The patent introduces an agent hub as an intermediary component that mediates between AI models on different user terminals. The agent hub receives AI model information from various devices, validates it through authentication, and distributes it to other terminals. This intermediary structure ensures that synchronization occurs through a controlled gateway rather than direct peer-to-peer communication, thereby maintaining information security while achieving service consistency across devices.
2Adaptability or versatility
If multiple AI agents are managed across external devices and cloud environment, then service versatility and adaptability are improved, but system complexity increases
Solution Approach 1:
The patent segments the AI agent management system into distinct components: local AI agents on external devices, a cloud-based agent hub, and intermediate communication interfaces. Each segment handles specific functions independently - local agents process device-specific tasks, while the cloud hub manages coordination and authentication. This segmentation allows the system to support multiple devices and services without creating monolithic complexity, as each component remains relatively simple and focused.
3Duration of action of moving object
If AI agent information is transmitted between user terminal and external device, then service continuity is improved, but data loss and synchronization errors increase
Solution Approach 1:
The patent implements feedback mechanisms in the AI model synchronization process. The agent hub sends AI model information to external devices and receives acknowledgments confirming successful reception and installation. If acknowledgment is not received or synchronization fails, the system can retransmit the information. This feedback loop ensures that information is reliably transmitted and synchronized across devices, preventing data loss and maintaining service continuity.
Data Source
AI summary
Disclosed are a system for an artificial intelligence agent and an operating method thereof. An operating method of a mobile-centric agent hub system (MCAHS) may include registering and authenticating AI agents included in an external device, determining a task by analyzing an instruction received from a user, selecting an AI agent for processing the determined task, among the registered AI agents, transmitting the determined task to the selected AI agent, receiving the results of processing of the transferred task from the selected AI agent, and providing a final response generated based on the received results of the processing to the user.