Digital Twin Anomaly Detection Patents: Who Leads 2026
Filing growth compares 2021 (2 records) with 2024 (0) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field.
What this landscape covers
This landscape tracks patent filings that combine twin-based anomaly detection — feature generation, root-cause identification, and diagnostic routines run against a virtual asset model — with an underlying digital twin, cyber-physical system, or virtual asset architecture. The scope spans two distinct implementation contexts: heavy mobile equipment (excavators, machinery) and building or industrial control systems, which is why the IPC composition splits between excavating classifications and general-purpose data processing.
The dataset covers 16 published records dated 2015 through the 2026-07-31 cut-off. Because publication trails filing by roughly a year and a half, the most recent one to two years understate real filing activity and should be read as provisional rather than as evidence of a slowdown.
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Filing trend and technology composition
Sixteen records, a single-digit set of assignees, and an IPC mix split between mobile-equipment and software classifications — this is a narrow, concentrated corpus rather than a sprawling one.
Filing trend: a sharp 2022 peak
Filings were flat near zero through 2017-2020, rose to a peak of 14 records in 2022, then dropped to 0 by 2024 — a -100% swing over that three-year span. Because 2025 and 2026 publications are still arriving, this should be read as a filing pulse concentrated around 2021-2022 rather than a technology in decline.
IPC composition: mobile equipment meets data processing
E02F (excavating and earth moving) and G06F (electric digital data processing) each appear in 43.8% of the 16 records, with G05B (control and regulating systems) close behind at 31.3%. F24F (air conditioning and ventilation) and G01R (electric and magnetic measurement) appear in a smaller share, marking narrower application niches rather than core claim territory.
Shares are the percentage of the 16 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Digital Twins — Twin-Based Anomaly Detection Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about digital twins — twin-based anomaly detection patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaMost-cited records in this corpus
Building data platform with digital twin diagnostics (US20230359176A1)
The filing describes a building system that stores a digital twin — a virtual representation of a piece of building equipment — which communicates with that equipment to operate it, determine diagnostic messages from the virtual model, and send those messages back to the equipment to trigger a response action.Filed by Tyco Fire & Security GmbH, published 2023-11-09.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20230075005A1 | Intelligent asset anomaly prediction via feature generation | 12 |
| 2 | US20230358429A1 | Building data platform with digital twin-based diagnostic routines | 12 |
| 3 | US20230168961A1 | Systems and methods for identifying machine anomaly root cause | 9 |
| 4 | US11899527B2 | Systems and methods for identifying machine anomaly root cause based on a selected reduced order model and a … | 4 |
| 5 | US20230359176A1 | Building data platform with digital twin diagnostics | 3 |
| 6 | US20230359189A1 | Building data platform with digital twin functionality indicators | 1 |
Citation counts inside a searched corpus favour older filings — treat this as a signal of influence within the dataset, not a ranking of current technical importance.
Publication numbers are shown where the record carries one (6 of 6 rows); clicking a row searches Eureka by that number.
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Browse MCP servers →What the numbers mean for a filing decision
Three findings shape where a new filer would actually have room to move in this art.
No long tail to watch
The ranked assignee list closes at three companies, and between them they account for every one of the 16 records in scope. There is no fragmented field of small filers to monitor — competitive attention should focus entirely on these three portfolios.
A concentrated filing window, not a steady climb
Activity clustered heavily around 2022 rather than building gradually. Combined with the drop to 0 by 2024, this reads as a short, intense filing push tied to specific product launches rather than an evenly maturing field.
Two claim territories, not one
Excavating equipment (E02F) and general data processing (G06F) tie as the largest IPC classes, each touching close to half of all records. A filer entering this space needs to decide whether the claim sits on the equipment side or the software/diagnostic-logic side, since the corpus is genuinely split between the two.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to digital twins — twin-based anomaly detection patent landscape, with the prior art for and against each one.
Where to take this analysis
The dataset points to a narrow, closed field with a short filing pulse rather than a steadily growing one — the practical next steps follow from that shape.
Watch the three incumbents directly
With the entire corpus held by three assignees, portfolio-level monitoring of those three names will catch nearly everything relevant, including any resumed filing once the current publication gap clears.
Explore assignee portfolios in EurekaCheck freedom-to-operate on the thinner IPC branches
F24F and G01R carry far fewer records than the excavating and data-processing classes. Before filing into HVAC-specific or sensor-measurement twin diagnostics, confirm those gaps reflect genuine white space rather than pending applications not yet published.
Run a freedom-to-operate search in EurekaRe-check the trend once 2025-2026 fully publish
The apparent drop to zero by 2024 sits right at the edge of the publication lag window. A follow-up pull in twelve to eighteen months will show whether the 2022 peak was a one-off pulse or the start of a new filing cycle.
Set a monitoring alert in EurekaCommon questions on this landscape
The ranked assignee list for this dataset contains three companies, and together they account for all 16 records in scope. This is not a top-50 or top-100 cut — it is the complete ranked set the data returns, meaning there is no meaningful long tail of smaller filers to track separately. Anyone doing competitive monitoring in this space can focus attention on those three portfolios rather than scanning a broad field.
Filings peaked at 14 records in 2022 and fell to 0 by 2024, a -100% change over that span. However, publication typically lags actual filing by around 18 months, so 2025 and 2026 figures are still incomplete and should not be read as a genuine decline yet. The safest interpretation is that 2021-2022 saw a concentrated filing push, and whether that pace resumes will only be clear once later years finish publishing.
The corpus splits mainly between excavating and earth-moving equipment (E02F, 43.8% of the 16 records) and general electric digital data processing (G06F, also 43.8%), with control and regulating systems (G05B) close behind at 31.3%. Smaller shares appear in air conditioning and ventilation (F24F) and electric measurement (G01R). This mix shows the field spans both physical heavy-equipment diagnostics and the software logic that interprets twin data, rather than sitting in one narrow discipline.
US20230359176A1, filed by Tyco Fire & Security GmbH and published 2023-11-09, covers a building system that stores a digital twin of a piece of building equipment, uses that virtual representation to determine diagnostic messages, and sends those messages back to the equipment to trigger an operational response. The claim scope centres on the closed loop between the twin's diagnostic output and the physical equipment's behaviour, not merely on maintaining a virtual model for monitoring purposes. Anyone building a twin-based diagnostic system that feeds decisions back into equipment operation should review this filing closely.
Based on IPC composition, the thinner branches are air conditioning and ventilation (F24F, 12.5% of 16 records) and electric and magnetic measurement (G01R, 6.3%), both well below the roughly 44% coverage of the two leading classes. That gap suggests HVAC-specific twin diagnostics and sensor-level measurement-driven anomaly models are comparatively under-claimed. A freedom-to-operate check is still advisable before treating these as fully open, since low record counts can also reflect pending unpublished applications.
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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.