# Managing AI and Machine Learning on Many Devices from the Cloud > 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. - **Patent:** US 12111744 - **Original title:** Cloud-based fleet and asset management for edge computing of machine learning and artificial intelligence workloads - **Owner:** Armada Systems - **Granted:** 2024 - **Status:** Active - **Times cited:** 5 - **Field:** consumer_electronics, software, telecommunications, ai_ml, automotive, industrial_iot ## What it does This patent details a system for managing a 'fleet' of edge devices, which are small computers or sensors that perform tasks locally. It works by receiving monitoring information about AI or machine learning programs running on these edge compute units, as described in claim 1. It also collects status information from connected edge assets, such as cameras or environmental sensors. All this data is shown on a remote graphical user interface (GUI) in a cloud environment, allowing a user to see how a selected group of devices is performing. The user can then provide input through the GUI to update the configuration of an AI or machine learning workload on specific edge devices. For example, a user could tell a group of factory robots to update their object recognition model (a pre-trained ML model) to better identify new product defects, with the cloud system transmitting the necessary control information, as outlined in claim 1. ## What it does NOT cover - Does not cover managing individual edge devices without a central cloud-based GUI for fleet-wide oversight and configuration. - Does not cover systems where the AI/ML model updates are not initiated by a user configuration input received via a remote GUI. - Does not cover edge device management where the updated configuration is not specifically for a pre-trained ML or AI model or network connectivity. - Does not cover systems that only monitor edge devices without the capability to transmit control information for updated configurations. - Does not cover local, on-device management of AI/ML workloads without interaction with a cloud computing environment. ## The clever bit The novelty lies in providing a unified, cloud-based graphical interface to not only monitor a diverse fleet of edge devices and their AI workloads, but also to centrally push complex updates like local retraining, finetuning, or distributed learning orchestration back to specific devices or groups of devices. ## Real-world examples 1. Autonomous vehicle fleets updating their perception models 2. Smart factory robots receiving new defect detection algorithms 3. Remote sensor networks for environmental monitoring adjusting their data analysis models 4. Retail store cameras updating their customer behavior analytics AI 5. Industrial IoT deployments managing predictive maintenance models on machinery ## Why it matters Managing vast numbers of smart devices, especially those running complex AI or machine learning tasks, is a significant challenge. This patent offers a structured way to centrally monitor and update these distributed systems. It is particularly relevant for industries deploying large-scale IoT (Internet of Things) solutions, where manual updates for each device are impractical. This approach helps ensure that AI models on edge devices remain accurate and efficient without needing physical access to each unit. ## Frequently asked questions ### What does Managing AI and Machine Learning on Many Devices from the Cloud cover? 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. ### Who owns patent US 12111744? Armada Systems owns this patent, granted in 2024. ### When does this patent expire? This patent is expected to expire on January 8, 2044, when the invention enters the public domain. ### What is patent US 12111744 cited by? This patent has been cited by 5 later patents that build on its ideas. ### What problem does this patent solve? Managing vast numbers of smart devices, especially those running complex AI or machine learning tasks, is a significant challenge. This patent offers a structured way to centrally monitor and update these distributed systems. It is particularly relevant for industries deploying large-scale IoT (Internet of Things) solutions, where manual updates for each device are impractical. This approach helps ensure that AI models on edge devices remain accurate and efficient without needing physical access to each unit. ### What does this patent NOT cover? Does not cover managing individual edge devices without a central cloud-based GUI for fleet-wide oversight and configuration. **Full plain-English explainer:** https://patentbrief.org/patent/us/12111744/cloud-based-fleet-and-asset-management-for-edge-computing-of-machine-learning-an-12111744 **Original patent:** https://patents.google.com/patent/US12111744 --- _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. - [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 a Cloud Server Manages AI Services on Local Edge Devices](https://patentbrief.org/patent/us/20260156193/service-management-method-and-system-and-configuration-server-and-edge-computing) — 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. - [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 AI at the Edge Learns and Adapts Its Brain](https://patentbrief.org/patent/us/20250292091/systems-and-methods-for-dynamic-neural-network-enhancement-and-adaptive-edge-com) — This patent describes how an artificial intelligence system running on a small device can automatically improve its accuracy and efficiency by changing its internal structure and learning methods in real-time.