An intelligent gateway device based on AI edge computing

By introducing adaptive task scheduling, heterogeneous resource management, and dual-path model verification into the edge computing gateway, the problems of low resource scheduling efficiency, power consumption mismatch, and insufficient model security are solved, thus realizing a high-performance, high-efficiency, and high-security edge computing gateway.

CN121979685BActive Publication Date: 2026-07-07SUZHOU WENLIAN TECH CO LTD
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Patent Information

Authority / Receiving Office
CN ยท China
Patent Type
Patents(China)
Current Assignee / Owner
SUZHOU WENLIAN TECH CO LTD
Filing Date
2026-04-03
Publication Date
2026-07-07

AI Technical Summary

Technical Problem

Existing edge computing gateways suffer from low resource scheduling efficiency, mismatch between power consumption and performance, and insufficient security in AI model execution, especially in industrial scenarios where they struggle to meet the response latency and model security requirements of time-sensitive tasks.

Method used

By employing an adaptive task scheduling engine, a heterogeneous resource dynamic orchestration module, an adaptive power management module, and a dual-path model verification and execution module, the system achieves collaborative scheduling of heterogeneous resources, dynamic power management, and end-to-end trusted model verification, forming an intelligent and adaptive internal management system.

Benefits of technology

It improves the response speed of critical tasks, reduces latency and energy waste, ensures the safety and reliability of AI models, and achieves the best balance between performance and power consumption.

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Abstract

The application belongs to the technical field of Internet of Things, and discloses an intelligent gateway device based on AI edge computing, which comprises a main processor, an AI acceleration processor, a self-adaptive task scheduling engine, a heterogeneous resource dynamic arrangement module, a self-adaptive power consumption management module, and a two-way model verification and execution module running in a hardware trusted execution environment. The task scheduling engine queues according to the task priority; the resource arrangement module accurately schedules the task to the CPU or the AI processor according to the task characteristics; the power consumption management module dynamically adjusts the power consumption according to the load state of the task queue; and the security module verifies the source and function of the AI model before execution. Through the deep cooperation and closed-loop control of the four modules, the application realizes the high real-time processing performance, the extreme energy efficiency ratio and the solid security guarantee of the intelligent gateway device.
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