Gas Sensor Drift Patents: Leaders, Trends & White Space 2026
A data-backed look at gas sensor drift patents: who leads filings, where the field is concentrated, and where under-claimed white space remains through 2026.
Filing growth = 2021 (27 records) → 2024 (20); 2024 is the last year we treat as complete. Top-5 share = the 5 largest assignees ÷ all 951 records in scope (CR5), not the ranked leaders only.
What the gas sensor drift patent landscape covers
Gas sensor drift is the slow change in a sensor’s baseline or sensitivity over time, and the patents in this landscape address it from two directions: correcting for drift computationally (calibration models, estimation algorithms, adjustment routines applied to sensor output) and reducing drift at the hardware level (materials, packaging, and flow-path design that make the underlying sensor more stable). The search covers 951 published records with claims or titles explicitly tied to gas sensor drift or sensor drift combined with gas measurement.
The dataset spans priority years from 2015 through the 2026 cut-off, with receiving offices concentrated in the United States, Europe and the WIPO PCT system, alongside meaningful India, UK and Germany filings. Because publication lags filing by roughly 18 months, the most recent one to two years understate true filing activity.
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Filing trends and technology composition
Two views anchor this landscape: how filing volume has moved year over year, and how the 951 records split across IPC subclasses. Both use the same record set, so the shares are directly comparable.
Filing trend, 2017-2026
Filings rose from 35 in 2017 to a peak of 90 in 2019, then eased back. The most recent complete three-year comparison, 2021 to 2024, shows a 26% decline (27 to 20 records) — a real cooling from the 2019 peak, though 2025-2026 figures are still filling in as publications catch up to filing dates.
Publication lags filing by roughly 18 months, so 2025 onwards are still filling in. Growth rates on this page therefore end at 2024; running them to the last bar would understate the field.
Technology composition by IPC subclass
G01N (material analysis and testing) accounts for 50.2% of the 951 records in scope, making it the dominant claim territory by a wide margin. A61B (diagnosis and surgery) follows at 10.8%, then a cluster of control-systems and measurement subclasses — G05B, G05D, G01L, F02D and G01D — each sitting between 4.7% and 6.0%. Records can carry multiple IPC codes, so these shares sum to more than 100%.
Shares are the percentage of the 951 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
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Try EurekaRepresentative filing and most-cited prior art
Methods, apparatuses, and systems for gas sensor drift adjustment (US20260177537A1)
The filing describes receiving a plurality of sensor measurements from a gas sensor over a sampling period, generating sampled sensor data that meets a set of operational conditions and a sample size threshold, then producing estimated drift data from that sampled data constrained by one or more drift constraints. The estimated drift data is stored and used to adjust the gas sensor's output via a drift adjustment model.Filed by Honeywell International Inc., published 2026-06-25.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US5475610A | Thermal cycler for automatic performance of the polymerase chain reaction with close temperature control | 796 |
| 2 | US5062446A | Intelligent mass flow controller | 346 |
| 3 | US20080135044A1 | Methods and devices for minimally invasive respiratory support | 252 |
| 4 | EP0488769A2 | Thermal cycler for automatic performance of the polymerase chain reaction with close temperature control | 206 |
| 5 | US5048515A | Respiratory gas supply apparatus and method | 191 |
| 6 | US20020092779A1 | Drift compensation for gas component sensors | 169 |
| 7 | US20060155486A1 | Computer-implemented system and method for analyzing mixtures of gases | 154 |
| 8 | US20110264353A1 | Model-based optimized engine control | 140 |
| 9 | US20020072112A1 | Thermal cycler for automatic performance of the polymerase chain reaction with close temperature control | 137 |
| 10 | US3939654A | Engine with dual sensor closed loop fuel control | 135 |
Citation counts favour older records simply by virtue of being searchable longer; treat them as a signal of influence on the field, not of current commercial importance.
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Browse MCP servers →What the numbers mean for a filing decision
The concentration and technology figures point to a field that is moderately consolidated at the top but still has real room to file outside the densest claim territory.
Leadership is present but not dominant
The top 5 assignees combined hold 119 records, 12.5% of all 951 records in scope; the top 10 add up to 193 records, 20.3% of the field. The leader alone holds 31 records, with fifth place at 18 and tenth at 13 — a gap wide enough that a new entrant with a strong hardware or calibration approach is not competing against a single dominant blocker.
Material analysis and testing is the crowded ground
Half of all records in scope sit in G01N, the material-analysis-and-testing subclass, meaning most drift-correction and sensor-stability claims are being litigated for space there. Filing a broad G01N claim now means competing against the densest prior art in the field.
Volume has cooled from its 2019 peak
After peaking at 90 filings in 2019, the field fell to 27 filings in 2021 and 20 in 2024 — a documented 26% decline over that span. This is the last window with complete publication data; treat 2025 and 2026 figures as still filling in rather than as evidence of a continued slide.
Control and measurement subclasses are thinner
G05B, G05D, G01L and G01D each hold between 4.7% and 5.8% of the 951 records, well below G01N and A61B. Drift-correction approaches framed as control-system or general-measurement inventions face noticeably less claim density than approaches framed as material analysis.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to chemical & gas sensors: gas sensor drift patent landscape, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| Shandong Nova Fitness Electronic Technology Co., Ltd. | OGRANDS INNOVATION INC | 22 |
| Fujikin Incorporated | Tokyo Electron Limited | 13 |
| Fujikin Incorporated | OHMI TADAHIRO | 6 |
| Tokyo Electron Limited | OHMI TADAHIRO | 6 |
| Fujikin Incorporated | International Foundation for the Advancement of Science (public interest foundation) | 5 |
| Tokyo Electron Limited | International Foundation for the Advancement of Science (public interest foundation) | 5 |
| Honeywell International Inc. | WILLETT MARTIN JOHN | 3 |
| Honeywell International Inc. | PRATT KEITH FRANCIS EDWIN | 3 |
Ten co-assignee pairs appear in the dataset; the strongest pairing files jointly on 22 records, suggesting at least one active cross-entity development relationship worth tracking for freedom-to-operate purposes.
Where to take this analysis
The dataset points to specific next steps depending on whether you are scouting freedom to operate, benchmarking a competitor, or looking for a filing angle.
Map the white space in adjacent subclasses
G05B, G05D, G01L and G01D each carry a fraction of G01N's density. A drift-correction claim framed around control-system logic rather than material analysis has more open ground to work with.
Explore white space in EurekaTrack the leading filer's recent claim language
With 31 records, the leading assignee sets the tone for what a defensible drift-adjustment claim looks like today, including the most recent 2026 filing.
Review claim language in EurekaWatch the co-filing relationships
The strongest co-assignee pairing spans 22 joint records, a signal of an active development partnership that competitors and licensors should factor into any FTO review.
Trace assignee relationships in EurekaCommon questions about the gas sensor drift patent landscape
The dataset in scope contains 951 published records with claims or titles tied to gas sensor drift, spanning priority years from 2015 through the 2026 data cut-off. This includes both computational drift-correction approaches and hardware- or materials-based stability improvements. Because publication lags filing by roughly 18 months, the most recent one to two years will likely see upward revision as more filings publish.
The leading assignee holds 31 records in the ranked field of 100 companies, with the fifth-ranked assignee at 18 and the tenth at 13. The top 5 assignees combined account for 12.5% of all 951 records, and the top 10 account for 20.3% — a moderate concentration that leaves substantial room for filers outside the leading group rather than a single dominant blocker.
Filing volume peaked in 2019 at 90 records and has since cooled; the most recent complete comparison, 2021 to 2024, shows a 26% decline from 27 to 20 filings. Figures for 2025 and 2026 are still filling in due to publication lag, so they should not yet be read as a continuation of that decline. The honest read is that the field has passed its filing peak but has not collapsed.
G01N, material analysis and testing, covers 50.2% of the 951 records in scope, making it by far the densest claim territory. A61B, diagnosis and surgery, follows at 10.8%, reflecting the significant medical-device use case for gas sensing. A cluster of control-systems and measurement subclasses — G05B, G05D, G01L, F02D and G01D — each hold between 4.7% and 6.0%, offering comparatively thinner prior art for control-framed drift-correction claims.
US20260177537A1, published 2026-06-25 and assigned to Honeywell International Inc., describes receiving gas sensor measurements over a sampling period, filtering them against operational conditions and a sample size threshold, generating estimated drift data constrained by one or more drift constraints, and then applying a drift adjustment model to correct the sensor's output. It sits within the broader computational drift-correction approach that runs through much of the G01N-classified portion of this landscape. Anyone building a similar adjustment pipeline should review its specific constraint and threshold language closely.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.