Managing and Updating AI on Many Smart Devices from the Cloud
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.
Original patent title: “Cloud-based fleet and asset management for edge computing of machine learning and artificial intelligence workloads”
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. Granted to Armada Systems in 2024 with 20 claims and 21 forward citations, and it is expected to expire in 2043.
Coverage
What does this patent actually cover?
This patent describes a method for managing many smart devices, called a 'fleet of edge devices,' that run artificial intelligence (AI) or machine learning (ML) programs. It works by receiving 'monitoring information' about the AI programs and 'status information' from each device (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1). This information is then shown on a 'remote fleet management graphical user interface (GUI)' in the cloud, allowing a user to see what's happening with a selected group of devices. The user can then provide 'user configuration inputs' through this GUI to update how an AI program works on one or more devices. For example, a user could tell a group of smart cameras to collectively 'retrain' their object recognition AI model using new data they've collected, with the cloud system sending 'orchestration information' to coordinate this distributed retraining (Claim 1). The system can also manage local retraining or fine-tuning of models on individual edge devices (Claim 4, 7).
The gap
What does this patent NOT cover?
- Does not cover managing a single edge device; it specifically requires a 'fleet of edge devices' (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1).
- Does not cover managing devices that do not implement 'machine learning (ML) or artificial intelligence (AI) workloads' (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1).
- Does not cover systems where the AI models are not 'pre-trained' before being deployed to the edge compute units (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1).
- Does not cover local management of edge devices without a 'remote fleet management graphical user interface (GUI)' in a cloud environment (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1).
- Does not cover systems where the updated configuration is not related to retraining or finetuning a pre-trained ML/AI model (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1, 4, 7, 10).
- Does not cover systems that only monitor edge devices without the ability to transmit control information for updated configurations (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1).
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The innovation lies in providing a centralized, cloud-based system to remotely monitor and, critically, *update* (retrain or finetune) pre-trained AI models across an entire fleet of distributed edge devices, even coordinating distributed retraining efforts among them.
The Patent Drawing
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Managing AI models on industrial robots in a smart factory
Updating object detection AI on a fleet of autonomous delivery vehicles
Controlling AI-powered security cameras across multiple retail stores
Orchestrating AI updates for smart city traffic sensors
Managing predictive maintenance AI on wind turbines in a wind farm
Why it matters
The bigger picture
As more AI and ML applications move from central data centers to 'edge devices' like smart sensors and robots, managing these distributed systems becomes complex. This patent addresses the challenge of keeping many AI models updated and performing well across a large network of devices. It allows for centralized control and updates, which is crucial for maintaining performance and security in large-scale deployments like smart factories or autonomous vehicle fleets.
Filed
September 5, 2023
Granted
January 16, 2024
Market context
Who's building on this
Companies in this space
Major cloud providers like Amazon Web Services (AWS) with services like AWS IoT Greengrass, Microsoft Azure with Azure IoT Edge, and Google Cloud with Google Cloud IoT Core are actively developing and offering similar capabilities for managing and deploying AI/ML workloads on edge devices. Specialized companies focusing on industrial IoT and edge AI platforms also operate in this space, building solutions for various industries.
Market impact
This patent addresses a growing need in the market for efficient management of AI at the edge. The ability to remotely update and retrain AI models on distributed devices helps reduce operational costs and improves the longevity and adaptability of edge AI deployments. It enables industries to deploy more sophisticated AI solutions outside of traditional data centers, fostering the growth of smart factories, autonomous systems, and advanced IoT applications.
Claim 1 — Plain English
What this patent covers
This patent describes a method for managing many smart devices, called a 'fleet of edge devices,' that run artificial intelligence (AI) or machine learning (ML) programs. It works by receiving 'monitoring information' about the AI programs and 'status information' from each device (Claim 1). This information is then shown on a 'remote fleet management graphical user interface (GUI)' in the cloud, allowing a user to see what's happening with a selected group of devices. The user can then provide 'user configuration inputs' through this GUI to update how an AI program works on one or more devices. For example, a user could tell a group of smart cameras to collectively 'retrain' their object recognition AI model using new data they've collected, with the cloud system sending 'orchestration information' to coordinate this distributed retraining (Claim 1). The system can also manage local retraining or fine-tuning of models on individual edge devices (Claim 4, 7).
The clever bit
The innovation lies in providing a centralized, cloud-based system to remotely monitor and, critically, *update* (retrain or finetune) pre-trained AI models across an entire fleet of distributed edge devices, even coordinating distributed retraining efforts among them.
What it does not cover
- Does not cover managing a single edge device; it specifically requires a 'fleet of edge devices' (Claim 1).
- Does not cover managing devices that do not implement 'machine learning (ML) or artificial intelligence (AI) workloads' (Claim 1).
- Does not cover systems where the AI models are not 'pre-trained' before being deployed to the edge compute units (Claim 1).
- Does not cover local management of edge devices without a 'remote fleet management graphical user interface (GUI)' in a cloud environment (Claim 1).
- Does not cover systems where the updated configuration is not related to retraining or finetuning a pre-trained ML/AI model (Claim 1, 4, 7, 10).
- Does not cover systems that only monitor edge devices without the ability to transmit control information for updated configurations (Claim 1).
Patent timeline
Application submitted to the patent office
Application published, typically 18 months after filing
Patent officially issued
Patent enters public domain
PatentBrief Score
Impact Score
Strong
Citation count
27/40
Moderately cited
Claim breadth
13/20
Broad claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
20/20
Granted within 5 years
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$164K – $524K
Midpoint $328K · 17.0 yr remaining · industry ×1.4
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
The original legal language
Original claims
20 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
Prabhakara, J., Mishra, P. K., Swaminathan, A., & Nair, P. (2024). Managing and Updating AI on Many Smart Devices from the Cloud (U.S. Patent No. 11,876,858). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/11876858/cloud-based-fleet-and-asset-management-for-edge-computing-of-machine-learning-an
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does Managing and Updating AI on Many Smart Devices from the Cloud cover?
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.
Who owns patent US 11876858?
Armada Systems owns this patent, granted in 2024.
When does this patent expire?
This patent is expected to expire on September 5, 2043, when the invention enters the public domain.
What is patent US 11876858 cited by?
This patent has been cited by 21 later patents that build on its ideas.
What problem does this patent solve?
As more AI and ML applications move from central data centers to 'edge devices' like smart sensors and robots, managing these distributed systems becomes complex. This patent addresses the challenge of keeping many AI models updated and performing well across a large network of devices. It allows for centralized control and updates, which is crucial for maintaining performance and security in large-scale deployments like smart factories or autonomous vehicle fleets.
What does this patent NOT cover?
Does not cover managing a single edge device; it specifically requires a 'fleet of edge devices' (Claim 1).
Same assignee
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