Efficiently Combining Data from Different Sensors
This patent describes a system for combining information from many different types of sensors more efficiently by carefully selecting and processing the data, reducing the computer power needed.
Original patent title: “Systems and methods of sensor data fusion”
This patent describes a system for combining information from many different types of sensors more efficiently by carefully selecting and processing the data, reducing the computer power needed. Granted in 2026.
Coverage
What does this patent actually cover?
The system outlined in this patent collects data from multiple sensors, then carefully organizes and filters it, a process called curation. It links related pieces of data and combines them, which is known as fusion. A key part of this process is calculating 'conditional entropy' to decide which data is most important, which helps reduce the amount of computing power and time needed. The system then uses this combined data to make educated guesses or decisions (inference) and checks if the combined data is reliable enough by comparing it against a set mathematical standard (validation). For example, a robot could use this to combine camera images, lidar distances, and microphone sounds to understand its surroundings without slowing down.
The gap
What does this patent NOT cover?
- Does not cover sensor data fusion systems that do not curate or filter the raw data before combining it.
- Does not cover methods of data fusion that do not calculate conditional entropy to reduce computational load.
- Does not cover systems that combine data from only a single type of sensor.
- Does not cover systems that fuse data without validating the output against a mathematical threshold.
- Does not cover data fusion techniques that increase, rather than reduce, computational demand and processing time.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The clever part is reducing the computational effort required for data fusion. It achieves this by curating the data and calculating conditional entropy, which helps the system focus only on the most relevant information from multiple sensors, making the process much more efficient.
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
Autonomous vehicle navigation systems
Robotics for industrial automation
Smart home environmental monitoring
Wearable health tracking devices
Industrial IoT sensor networks
Why it matters
The bigger picture
Combining data from various sensors is critical for technologies like self-driving cars, smart homes, and advanced robotics. This patent focuses on making that process faster and less demanding on computer resources. By reducing computational demands, it allows for more complex real-time decision-making in devices with limited power or processing ability, which can lead to more responsive and reliable systems.
Filed
January 6, 2026
Granted
September 15, 2026
Market context
Who's building on this
Companies in this space
Companies heavily invested in AI, IoT, and autonomous systems are continuously developing and refining sensor data fusion techniques. Major players like Google, Amazon, and NVIDIA, along with automotive companies such as Tesla and Waymo, are actively working on systems that combine diverse sensor inputs for real-time decision-making in their products. Industrial automation firms like Bosch and Siemens also apply these principles in their smart factory solutions.
Market impact
The ability to efficiently fuse sensor data is fundamental to the advancement of many modern technologies. This focus on reducing computational demand could enable more sophisticated, real-time applications in areas like autonomous driving and advanced robotics, where quick and accurate decisions based on multiple data streams are essential. It contributes to making these complex systems more practical and widespread by lowering their processing requirements.
Claim 1 — Plain English
What this patent covers
The system outlined in this patent collects data from multiple sensors, then carefully organizes and filters it, a process called curation. It links related pieces of data and combines them, which is known as fusion. A key part of this process is calculating 'conditional entropy' to decide which data is most important, which helps reduce the amount of computing power and time needed. The system then uses this combined data to make educated guesses or decisions (inference) and checks if the combined data is reliable enough by comparing it against a set mathematical standard (validation). For example, a robot could use this to combine camera images, lidar distances, and microphone sounds to understand its surroundings without slowing down.
The clever bit
The clever part is reducing the computational effort required for data fusion. It achieves this by curating the data and calculating conditional entropy, which helps the system focus only on the most relevant information from multiple sensors, making the process much more efficient.
What it does not cover
- Does not cover sensor data fusion systems that do not curate or filter the raw data before combining it.
- Does not cover methods of data fusion that do not calculate conditional entropy to reduce computational load.
- Does not cover systems that combine data from only a single type of sensor.
- Does not cover systems that fuse data without validating the output against a mathematical threshold.
- Does not cover data fusion techniques that increase, rather than reduce, computational demand and processing time.
Patent timeline
Application submitted to the patent office
Patent officially issued
PatentBrief Score
Impact Score
Early stage
Citation count
0/40
No citations yet
Claim breadth
0/20
Narrow 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
$11K – $35K
Midpoint $22K · 19.2 yr remaining · industry ×0.9
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
Concepts involved
Cite this patent
(2026). Efficiently Combining Data from Different Sensors (U.S. Patent No. 12,737,436). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/12737436/systems-and-methods-of-sensor-data-fusion
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 Efficiently Combining Data from Different Sensors cover?
This patent describes a system for combining information from many different types of sensors more efficiently by carefully selecting and processing the data, reducing the computer power needed.
When does this patent expire?
This patent is expected to expire on September 15, 2046, when the invention enters the public domain.
What problem does this patent solve?
Combining data from various sensors is critical for technologies like self-driving cars, smart homes, and advanced robotics. This patent focuses on making that process faster and less demanding on computer resources. By reducing computational demands, it allows for more complex real-time decision-making in devices with limited power or processing ability, which can lead to more responsive and reliable systems.
What does this patent NOT cover?
Does not cover sensor data fusion systems that do not curate or filter the raw data before combining it.
Patent monitoring