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Run your analysis now →https://www.patsnap.com/resources/blog/rd-blog/precision-livestock-farming-sensors-patent-landscape/ · Patsnap · data cut-off 2026-07-31 · downloaded from the live page
Patent Landscape · Livestock FarmingPrecision Livestock Farming Sensors: Patents Behind Collars, Ear Tags and Behaviour Models
- A crowded top five. The five leading assignees together hold 41.9% of all 31 records in scope, with the leader alone at 7 filings — so freedom-to-operate work has to start with a small cluster, not a long list.
- Filing is recent and concentrated. Activity was near zero in 2017 and peaked at 12 records in 2025, meaning almost the entire dataset reflects filings from the last few years rather than a mature, settled field.
- Two IPC classes dominate the claim space. A01K (animal husbandry) and A61B (diagnosis and surgery) each cover roughly two-thirds of the 31 records, while transmission and AI-model classes sit under 10% — a sign of where claims are thin.
31
Published Records
42%
Top-5 Share of All Records
IN
Leading Jurisdiction
41
Active Filers Ranked
Top-5 share is the combined record count of the five largest assignees divided by all 31 records in scope (CR5), not by the ranked leaders only.
Published byPatsnap Research··7 min readSourced from Patsnap Eureka
Field Overview
What this dataset covers
Precision livestock farming sensors sit at the intersection of wearable hardware and veterinary diagnostics: accelerometer collars and ear tags that capture movement data, plus the algorithms that turn that data into behaviour classification, body condition scoring or fertility state. The 31 records in scope span filings from 2015 through the 2026 cut-off, drawn from applicants ranging from university veterinary groups to standalone AI ventures. Most of the claim activity clusters around animal husbandry hardware and diagnostic methods, rather than the data transmission or AI-model layers that sit downstream of the sensor itself.
Because publication lags filing by roughly 18 months, the 2025 and 2026 figures in this dataset are undercounts of actual filing activity in those years, not a sign that the field is slowing down.
Filing activity and technology composition, 2015-2026
Source: Patsnap Eureka. Assignee ranking and totals. Derived from a Patsnap search on Precision Livestock Farming Sensors covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
The Numbers
Filing trend and technology mix
Two views of the same 31-record dataset: how filing activity has moved year over year, and which IPC subclasses carry the claim weight.
A field that only recently started filing
Filings were flat at zero in 2017 and did not build momentum until the run-up to a peak of 12 records in 2025. With fewer than four complete years of meaningful activity once publication lag is accounted for, no growth rate can be stated reliably from this trend alone.
Husbandry and diagnostics carry the claim weight
A01K (animal husbandry & fishing) and A61B (diagnosis & surgery) each appear in over two-thirds of the 31 records, with A61D (veterinary instruments) close behind at 35.5%. Healthcare informatics, business-process data handling, AI models and digital transmission each sit under 17%, which is a narrower base than the hardware side of the field.
Shares are the percentage of the 31 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Source: Patsnap Eureka. Filing trend and technology composition. Derived from a Patsnap search on Precision Livestock Farming Sensors covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.
Go deeper on Precision Livestock Farming Sensors with Eureka
This page is one run against one query. Ask Eureka your own question about precision livestock farming sensors and every answer comes back with the patent numbers behind it.
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The most-cited records in this dataset
Representative Filing
Improved method and relevant apparatus for the determination of the body condition score, body weight and state of fertility
LIVESTOCK 3D S.A.
The method calculates body condition score, weight and fertility state through mathematical processing of an animal's morphological profile, captured by a contact or no-contact detection device and interpreted by a specific mathematical method. The scoring approach is designed to be independent of species, race, gender, age and absolute size of the examined animal.Filed by Livestock 3D S.A., published 2018-02-15.
Highest-citation records
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | WO2011120529A1 | Model for classifying an activity of an animal | 42 |
| 2 | US20180042584A1 | Improved method and relevant apparatus for the determination of the body condition score, body weight and sta… | 40 |
| 3 | US10639014B2 | Method and relevant apparatus for the determination of the body condition score, body weight and state of fer… | 6 |
| 4 | WO2024176006A1 | Aviary monitoring system and method of monitoring a broiler aviary | 2 |
Citation counts inside this corpus favour older records and should be read as a signal of influence within the dataset, not as a measure of current commercial importance.
Publication numbers are shown where the record carries one (4 of 4 rows); clicking a row searches Eureka by that number.
Source: Patsnap Eureka. Citation counts and representative records. Derived from a Patsnap search on Precision Livestock Farming Sensors covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
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What the data implies for decision-making
Three read-throughs from the concentration, trend and citation figures above.
Concentration
41.9%
of 31 records held by top 5
A small cluster to clear before filing
With the leading assignee at 7 filings and the top five together holding 41.9% of all 31 records, a freedom-to-operate review in this space has a short, tractable list of parties to check first rather than a diffuse field.
Based on the assignee ranking of 41 companies
Timing
0 → 12
records, 2017 to peak year 2025
A field still building its prior art base
Activity moved from zero in 2017 to a peak of 12 records in 2025, which means most of what exists today was filed recently. Later years in the trend are undercounted because publication lags filing by about 18 months.
Peak year so far: 2025
Citations
42 citations
on the top-cited record
Older activity-classification work anchors the field
The most-cited record in this dataset addresses classifying animal activity, and the two next-highest-cited records both cover body condition and fertility scoring. New filings in behaviour classification or condition scoring are entering a space with established reference points already in place.
Citation counts favour older, earlier-searched records
Geography
16 of 31
records via India receiving office
Filing activity is not evenly split by jurisdiction
India accounts for the largest share of receiving offices in this dataset, ahead of WIPO/PCT, Israel and the United States, which should factor into where enforcement and freedom-to-operate checks are prioritised.
Receiving offices: India 16, WIPO 5, IL 4, US 2
Eureka AI Agent
Looking for what nobody has claimed yet?
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to precision livestock farming sensors, with the prior art for and against each one.
Source: Patsnap Eureka. Co-assignee relationships and derived observations. Derived from a Patsnap search on Precision Livestock Farming Sensors covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
Who's Filing
Assignee landscape
The ranking covers 41 companies counted in records, not a top-50 or top-100 cut — it is the full list the dataset returns. The top ten together account for 58.1% of all 31 records, with a long tail of single-filing entrants beyond that.
Leader
7 records
held by the top-ranked assignee
One clear leader, then a steep drop
The leading assignee holds 7 of the 31 records in scope, well ahead of fifth place at 1 record — a gap that marks a genuine leader rather than a crowded top tier.
Fifth place: 1 record; tenth place: 1 record
Tail
31 vs 41
records vs ranked companies
A long tail of single-filing entrants
Once past the top ten, most of the remaining ranked assignees hold a single record each, spanning university labs, individual inventors and early-stage AI ventures rather than established agtech incumbents.
Ranking covers 41 companies total
Collaboration
10 pairs
co-assignee relationships identified
Co-filing is limited and academic
The ten identified co-assignee pairs are dominated by university partnerships rather than corporate joint filings, suggesting most commercial applicants in this space are filing solo rather than through shared research agreements.
Strongest pairs link university co-assignees
Recent-year filing momentum
| Assignee | Recent year | YoY |
|---|---|---|
| SUNDARRASU S | 1 | — |
| Ingenera S.p.A. | 0 | — |
| PROPHET AI INC | 0 | -100% |
| Aalborg University | 0 | — |
| University of Copenhagen | 0 | — |
| Farm Robotics and Automation Ltd. | 0 | — |
| ZINAL M GOHIL | 0 | -100% |
| VIJAY M MANE | 0 | — |
Source: Patsnap Eureka. Assignee-level momentum. Derived from a Patsnap search on Precision Livestock Farming Sensors covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
What's Next
Where to take this analysis
The dataset points to specific next steps rather than general monitoring.
Check freedom-to-operate against the top cluster
With 41.9% of records held by five assignees, a targeted clearance review of that cluster's claims is more efficient than screening the full ranked list of 41 companies.
Explore assignee claims in EurekaWatch the transmission and AI-model classes
H04L and G06N each sit under 10% of the 31 records, well below the hardware-side classes — track new filings there before the space fills in.
Set up class monitoring in EurekaRevisit after the next publication cycle
Because 2025 and 2026 figures are understated by publication lag, re-running this analysis in a future cycle will surface filings not yet visible today.
Schedule a refresh in EurekaSource: Patsnap Eureka. Forward-looking reading of the same dataset. Derived from a Patsnap search on Precision Livestock Farming Sensors covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
FAQ
Common questions on this landscape
The leading assignee in this dataset holds 7 of the 31 records in scope, with the top five assignees together accounting for 41.9% of all records. Beyond the top ten, which together hold 58.1% of records, coverage thins into a long tail of single-filing entrants including university labs and individual inventors. This concentration pattern means freedom-to-operate work should prioritise the top cluster before screening the full 41-company ranking.
The dataset covers accelerometer collars, ear tag sensors, behaviour classification algorithms, and related claims around battery lifetime, data transmission and alert accuracy. IPC composition shows animal husbandry (A01K) and diagnostic methods (A61B) each present in over two-thirds of the 31 records, with veterinary instruments (A61D) close behind. Data transmission and AI-model classes are present in fewer than 10% of records, indicating those layers are less densely claimed.
Filing activity moved from zero records in 2017 to a peak of 12 records in 2025, which points to a field that only recently became active rather than one in decline. However, because publication lags filing by roughly 18 months, the most recent years in the trend understate actual filing activity. There are not yet four complete years of stable data to state a reliable growth rate.
US20180042584A1 covers a method and apparatus for determining body condition score, body weight and fertility state through mathematical processing of an animal's morphological profile, captured via a contact or no-contact detection device. It is one of the most-cited records in this dataset, with 40 citations, and its claims are designed to be independent of species, race, gender, age and size. Anyone building body condition scoring or fertility estimation from visual or contact sensor data should review its claim scope closely before finalising a similar approach.
The IPC composition shows data transmission (H04L), AI-model computing (G06N) and general data processing (G06F) each present in under 10% of the 31 records, well below the animal husbandry and diagnostic classes that dominate the field. This suggests claim space around low-power transmission protocols, AI-driven behaviour classification pipelines, and battery lifetime management for wearables remains comparatively open. A first claim in these areas would likely pair a specific hardware constraint, such as ear tag power budget, with a defined data-processing method rather than claiming the sensor hardware alone.
Answers are grounded in the same dataset. Derived from a Patsnap search on Precision Livestock Farming Sensors covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
Research Precision Livestock Farming Sensors in depth with Eureka
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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.