Industrial Equipment Data Organized into Smart Knowledge Graphs
Honeywell's patent describes a system that collects data from industrial equipment, makes sense of it using rules, and organizes it into a smart graph for better control and actions.
Original patent title: “Industrial knowledge graph and contextualization”
Honeywell's patent describes a system that collects data from industrial equipment, makes sense of it using rules, and organizes it into a smart graph for better control and actions. Owned by Honeywell International with 23 claims and 1 forward citation, and it is expected to expire in 2042.
Coverage
What does this patent actually cover?
This patent details a system for industrial settings that creates a 'knowledge graph' about equipment. It starts by receiving a request that includes a description of the equipment (an 'asset descriptor'). Then, it gathers operational data from various sources related to that equipment. The core innovation is 'contextualizing' this raw data using specific configuration details and rules. This means making the data understandable and relevant, like translating different machine languages into one common tongue. The processed data is then organized into a knowledge graph structure. Finally, the system can perform actions based on this organized knowledge, like adjusting equipment settings or flagging potential issues. For example, it could gather vibration data from a pump, combine it with its maintenance history and operating parameters, and then identify that a specific type of unusual vibration pattern indicates an imminent bearing failure, triggering an alert.
The gap
What does this patent NOT cover?
- Does not cover systems that collect data without contextualizing it using specific rules and configuration data.
- Does not cover knowledge graphs that are not specifically configured for the described industrial assets.
- Does not cover systems that do not perform actions based on the generated knowledge graph data.
- Does not cover the collection of data from non-operational technology sources.
- Does not cover knowledge graphs that are not organized within a defined data structure.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The real ingenuity lies in the 'contextualization' step. Instead of just collecting raw data, the system intelligently interprets it using specific rules and configuration data unique to the assets and their data sources, transforming disparate operational technology data into meaningful insights within a structured knowledge graph.
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
Industrial automation systems
Manufacturing plant monitoring
Energy grid management
Predictive maintenance platforms
Smart factory software
Why it matters
The bigger picture
In complex industrial environments, equipment generates vast amounts of data. This patent provides a structured way to make that data actionable. By creating a 'knowledge graph,' it allows for a deeper understanding of how different pieces of equipment and their data relate, which is crucial for optimizing operations, predicting failures, and improving safety in sectors like manufacturing and energy.
Filed
December 12, 2022
Market context
Who's building on this
Companies in this space
Honeywell International, the assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →, is a major player in industrial automation and control systems, and this technology likely forms part of their broader industrial IoT and digital transformation offerings. Other companies in the industrial software and IoT space, such as Siemens, GE Digital, and Rockwell Automation, are developing similar capabilities for managing and analyzing industrial data.
Market impact
This patent addresses the growing need for intelligent data management in industrial settings. By enabling the creation of contextualized knowledge graphs from operational data, it supports the development of more sophisticated predictive maintenance, process optimization, and autonomous control systems, driving efficiency and reducing downtime in heavy industries.
Claim 1 — Plain English
What this patent covers
This patent details a system for industrial settings that creates a 'knowledge graph' about equipment. It starts by receiving a request that includes a description of the equipment (an 'asset descriptor'). Then, it gathers operational data from various sources related to that equipment. The core innovation is 'contextualizing' this raw data using specific configuration details and rules. This means making the data understandable and relevant, like translating different machine languages into one common tongue. The processed data is then organized into a knowledge graph structure. Finally, the system can perform actions based on this organized knowledge, like adjusting equipment settings or flagging potential issues. For example, it could gather vibration data from a pump, combine it with its maintenance history and operating parameters, and then identify that a specific type of unusual vibration pattern indicates an imminent bearing failure, triggering an alert.
The clever bit
The real ingenuity lies in the 'contextualization' step. Instead of just collecting raw data, the system intelligently interprets it using specific rules and configuration data unique to the assets and their data sources, transforming disparate operational technology data into meaningful insights within a structured knowledge graph.
What it does not cover
- Does not cover systems that collect data without contextualizing it using specific rules and configuration data.
- Does not cover knowledge graphs that are not specifically configured for the described industrial assets.
- Does not cover systems that do not perform actions based on the generated knowledge graph data.
- Does not cover the collection of data from non-operational technology sources.
- Does not cover knowledge graphs that are not organized within a defined data structure.
Patent timeline
Application submitted to the patent office
Patent enters public domain
PatentBrief Score
Impact Score
Moderate
Citation count
6/40
Early citations
Claim breadth
15/20
Broad claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
0/20
Older than 20 years
Assignee scale
20/20
Major company or institution
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
$62K – $200K
Midpoint $125K · 16.5 yr remaining · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
The original legal language
Original claims
23 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
Pandurangan, G., KUMAR, M., PATEL, Z. G., & BURD, M. G. T. Industrial Equipment Data Organized into Smart Knowledge Graphs (U.S. Patent No. 20,230,195,095). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/20230195095/industrial-knowledge-graph-and-contextualization
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 Industrial Equipment Data Organized into Smart Knowledge Graphs cover?
Honeywell's patent describes a system that collects data from industrial equipment, makes sense of it using rules, and organizes it into a smart graph for better control and actions.
Who owns patent US 20230195095?
This patent is owned by Honeywell International.
When does this patent expire?
This patent is expected to expire on December 12, 2042, when the invention enters the public domain.
What is patent US 20230195095 cited by?
This patent has been cited by 1 later patents that build on its ideas.
What problem does this patent solve?
In complex industrial environments, equipment generates vast amounts of data. This patent provides a structured way to make that data actionable. By creating a 'knowledge graph,' it allows for a deeper understanding of how different pieces of equipment and their data relate, which is crucial for optimizing operations, predicting failures, and improving safety in sectors like manufacturing and energy.
What does this patent NOT cover?
Does not cover systems that collect data without contextualizing it using specific rules and configuration data.
Patent monitoring