# How a Cloud Server Manages AI Services on Local Edge Devices > This patent describes a system where a central cloud server helps set up and run Artificial Intelligence tasks on local devices, like smart cameras, by sending them specific AI programs and then displaying the results. - **Patent:** US 20260156193 - **Original title:** Service management method and system, and configuration server and edge computing device - **Owner:** BOE Technology Group Co - **Status:** Active - **Times cited:** 0 - **Field:** consumer_electronics, software, telecommunications, ai_ml, semiconductors ## What it does This system allows a cloud-based configuration server to manage Artificial Intelligence (AI) services on local edge computing devices. The configuration server provides a web page where a user can specify which edge computing device, terminal device, and AI service are needed. An AI service, which includes one or more 'edge applications,' is then deployed by the cloud server onto the chosen edge computing device, as described in claim 1. The edge computing device then acquires a multimedia data stream from a terminal device, like a camera, and uses the deployed AI application to process this data, performing 'application inference' to get a result. This result is sent back to the configuration server and then displayed on a connected display device. For example, a cloud server could deploy a facial recognition AI application to a local smart camera (edge device) to analyze video (multimedia data stream) from the camera (terminal device), then display alerts on a screen. ## What it does NOT cover - Does not cover systems where the AI service runs entirely on the cloud server without deployment to a local edge computing device, as claim 1 specifies the edge device performs inference. - Does not cover systems where the terminal device does not provide a 'multimedia data stream,' as this is explicitly required by claim 1 for the edge device to acquire. - Does not cover deployment methods that do not involve generating a configuration file, acquiring an executable file, a dynamic library, and an algorithm model, as specified in claims 2 and 3. - Does not cover systems where the configuration server, edge computing device, terminal device, and display device are all located in the same cloud environment, as claim 1 specifies edge, terminal, and display are 'local devices' and the server is a 'cloud device'. - Does not cover systems deploying non-AI services or applications that are not considered 'edge applications' within an AI service context. ## The clever bit The clever aspect is the centralized, streamlined management of complex AI services on distributed edge devices. It allows for flexible deployment and updates of AI applications, potentially as containerized images, from a single cloud interface, simplifying the operational burden of managing many remote AI-powered systems. ## Real-world examples 1. Smart city surveillance cameras performing real-time traffic analysis 2. Factory automation systems using AI for quality control on the production line 3. Retail store analytics systems tracking customer behavior with local cameras 4. Home security systems with AI-powered object detection on the camera itself 5. Agricultural monitoring systems using AI to analyze crop health from local sensors ## Why it matters This patent addresses a key challenge in modern computing: efficiently deploying and managing complex AI applications on many distributed local devices, often called 'edge computing.' By centralizing the configuration and deployment from a cloud server, it simplifies the process for businesses and organizations that need to run AI close to where data is generated, like in factories or smart cities. This approach can reduce network latency and improve data privacy by processing data locally. ## Frequently asked questions ### What does How a Cloud Server Manages AI Services on Local Edge Devices cover? This patent describes a system where a central cloud server helps set up and run Artificial Intelligence tasks on local devices, like smart cameras, by sending them specific AI programs and then displaying the results. ### Who owns patent US 20260156193? This patent is owned by BOE Technology Group Co. ### When does this patent expire? This patent is expected to expire on May 5, 2043, when the invention enters the public domain. ### What problem does this patent solve? This patent addresses a key challenge in modern computing: efficiently deploying and managing complex AI applications on many distributed local devices, often called 'edge computing.' By centralizing the configuration and deployment from a cloud server, it simplifies the process for businesses and organizations that need to run AI close to where data is generated, like in factories or smart cities. This approach can reduce network latency and improve data privacy by processing data locally. ### What does this patent NOT cover? Does not cover systems where the AI service runs entirely on the cloud server without deployment to a local edge computing device, as claim 1 specifies the edge device performs inference. **Full plain-English explainer:** https://patentbrief.org/patent/us/20260156193/service-management-method-and-system-and-configuration-server-and-edge-computing **Original patent:** https://patents.google.com/patent/US20260156193 --- _Source: PatentBrief — https://patentbrief.org. Patent facts are from public records; the plain-English explanation is PatentBrief's._ ## Related patents Semantically similar inventions in the PatentBrief corpus: - [Managing and Updating AI on Many Smart Devices from the Cloud](https://patentbrief.org/patent/us/11876858/cloud-based-fleet-and-asset-management-for-edge-computing-of-machine-learning-an) — This patent describes a system for remotely monitoring and updating artificial intelligence models running on a fleet of connected smart devices, like factory robots or smart cameras, all managed from a central cloud-based control panel. - [Managing AI and Machine Learning on Many Devices from the Cloud](https://patentbrief.org/patent/us/12111744/cloud-based-fleet-and-asset-management-for-edge-computing-of-machine-learning-an-12111744) — This patent describes a system for remotely monitoring and updating artificial intelligence and machine learning programs running on a large collection of smart devices, like robots or sensors, from a central cloud system. - [Running AI Models Locally on Edge Devices with Cloud Updates](https://patentbrief.org/patent/us/12033006/edge-deployment-of-cloud-originated-machine-learning-and-artificial-intelligence) — This patent describes a system for deploying AI models to local edge devices, allowing them to run and learn from local data, with the ability to send updates back to a central cloud for further model improvement. - [How to Update AI on Small Devices with Slow Internet](https://patentbrief.org/patent/us/20250363357/systems-and-methods-for-deploying-and-updating-neural-networks-at-the-edge-of-a-) — This patent describes a method for efficiently updating artificial intelligence models on small, internet-connected devices, like smart cameras, by sending only the changes, or 'patches,' instead of the entire updated model, which saves bandwidth. - [How 5G Networks Coordinate AI Models Across Different Devices](https://patentbrief.org/patent/us/20230412513/providing-distributed-ai-models-in-communication-networks-and-related-nodesdevic) — A method for 5G networks to translate AI requirements into network performance settings so that AI models can run efficiently across cloud, edge, and local devices.