Precision Agriculture Platform Irrigation Patent Snapshot
The patent corpus for precision agriculture platform irrigation is extremely small, with a single filer holding the dominant position across a corpus of only 6 patent families. Activity is heavily concentrated in the United States, with a secondary presence in India, and the technology mix blends horticulture, AI, and image-data processing.
One filer dominates a nascent, six-family corpus
COHEN HARRIS LEE holds 4 of the 6 patent families in scope, placing it unambiguously at the top of the ranking. The remaining two families are held by Indian academic institutions, Sri Venkateswara College of Engineering & Technology and Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology, each with 1 family.
The top five filers account for 100% of the ranked applicants visible in this query’ combined total — a concentration level that signals a pre-competitive or very early-stage space rather than an established industry battleground.
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 1 | COHEN HARRIS LEE | 4 | |
| 2 | SRI VENKATESWARA COLLEGE OF ENG & TECH | 1 | |
| 3 | Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology | 1 |
United States jurisdiction, though the small absolute corpus means any new entrant could rapidly alter the competitive balance.
The most recent filing years should be treated as under-counted due to standard patent publication lags; apparent inactivity in 2018–2024 and the single entries in 2025–2026 may not reflect the full picture of recent activity.
A 2017 filing cluster followed by a long quiet period, with AI and horticulture dominating the IPC mix
The annual trend and the technology composition together reveal a field that launched with a small burst of activity in 2017 and has since seen only isolated new entries, while the IPC breakdown shows dual emphasis on practical horticulture and computational AI methods.
Annual filing trend
Four families were filed in 2017, followed by zero activity recorded across 2018–2024, and single entries appearing in 2025 and 2026. Given publication lag, the 2025–2026 data points should be treated as incomplete; the apparent long gap between 2017 and recent years may narrow as pending applications publish.
↗ Hover for values · click a bar to ask EurekaTechnology composition
Both A01G (Horticulture & forestry) and G06N (Computing based on AI models) each appear across all 6 patent records, reflecting the platform’s core fusion of crop management and machine-learning methods. G06K (Data recognition & presentation) and G06T (Image data processing & generation) each appear in 4 records, confirming computer-vision pipelines as a key technical layer. A01B (Soil working in agriculture) appears in 3 records, while G06Q and G01N are the least-represented branches.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
Computer-implemented methods, computer readable me…
A computer platform implements a precision agriculture system that predicts output conditions, such as diseases, salt damage, soil problems, water leaks and generic anomalies, for orchards under analysis. The computer platform stores site and crop datasets and processed satellite image for the orchards. An orchard data learned model predicts a propensity… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Computer-implemented methods, computer readable me… | 26 |
| 2 | Computer-implemented methods, computer readable me… | 22 |
| 3 | Computer-implemented methods, computer readable me… | 4 |
| 4 | Computer-implemented methods, computer readable me… | 2 |
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents. Some patent titles may be shown in their original, non-English language where an accurate translation could not be guaranteed.
What the competitive structure means for R&D investment
With only 6 patent families and a single visible holder, this space presents both low barriers to entry and the risk of being blocked by an early-mover’s core claims in the US jurisdiction.
Life-cycle stage: nascent / pre-competitive
The lifecycle stage cannot be formally classified from the available evidence, but the corpus of 6 patent families with a primary filing cluster in 2017 and sparse subsequent activity points to a nascent or pre-competitive field. The absence of a large incumbent cohort means foundational claim positions remain largely unclaimed by major agri-tech players.
Early stageExtreme concentration in a tiny corpus
The top five filers hold 100% of the ranked applicants visible in this query’ combined total, with one entity — COHEN HARRIS LEE — accounting for 4 of the 6 patent families. This is a highly unusual concentration profile that reflects a field still in its patent-origination phase. A new entrant filing even a handful of well-scoped families could quickly become a co-leader.
High concentrationNo co-applicant activity recorded
Evidence pending: no co-filing or collaboration relationships appear in the current corpus. The two Indian academic institutions filing independently suggest academic interest without industry partnership, which may represent an opening for collaborative R&D agreements that could establish shared IP positions.
No co-filingsUS-centric with early Indian academic presence
The United States accounts for 4 patent records and India for 2. No other jurisdictions are represented, leaving major precision-agriculture markets in Europe, China, Brazil, and Australia entirely uncovered by existing filings. Any organization seeking global freedom-to-operate or market exclusivity in those regions faces minimal prior-art friction from this specific corpus.
US + India onlyGo beyond the landscape: Eureka’s TRIZ Solution agent breaks down an R&D problem and returns patented concept solutions, each with a technical approach and cited patent & literature evidence.
Co-filing pairs, ranked by the number of jointly-filed patent families.
Assignee snapshot from the current evidence set
The applicants below are visible in this query result. Because the evidence set is relatively small, read this section as a directional snapshot rather than a full competitive ranking.
COHEN HARRIS LEE
COHEN HARRIS LEE holds 4 patent families, all in the US jurisdiction, with technology emphasis concentrated in A01G 17 and A01G 25 (horticulture and forestry subclasses) and G06K 9 (data recognition). This profile suggests a platform centered on image-based crop and irrigation monitoring. Applicant momentum data is not available in the current evidence set.
families: 4Sri Venkateswara College of Engineering & Technology
Sri Venkateswara College of Engineering & Technology holds 1 patent family, with focus areas spanning A01B 79 (soil working), A01G 25 (irrigation), and G06N 20 (machine-learning methods). Its academic origin suggests exploratory research rather than a commercial prosecution strategy; applicant momentum data is not available in the current evidence set.
families: 1Frequently asked questions
The current corpus contains 6 patent families. This is a very small corpus, indicating the space is nascent and has not yet attracted broad filing activity from major agricultural technology companies.
COHEN HARRIS LEE is the leading filer with 4 patent families, all in the United States. The remaining 2 families are held by Sri Venkateswara College of Engineering & Technology and Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology, each with 1 family.
The United States accounts for 4 patent records and India for 2. No filings have been identified in Europe, China, Brazil, Australia, or other major agricultural markets, leaving those jurisdictions open from the perspective of this specific corpus.
The visible IPC classes are A01G (Horticulture & forestry) and G06N (Computing based on AI models), each appearing across all 6 patent records. G06K (Data recognition & presentation) and G06T (Image data processing & generation) each appear in 4 records, reflecting a strong computer-vision component. A01B (Soil working) appears in 3 records.
No co-applicant or collaboration relationships are recorded in the current corpus. All three filers have filed independently, and the two academic institutions show no industry partnership in their filings.
The two sparsest IPC branches within the corpus are G06Q (Business & admin data processing, 2 records) and G01N (Material analysis & testing, 1 record). These represent under-served adjacent areas where farm-management software and soil or water quality sensing intersect with precision irrigation platforms. Any assessment should also check broader agri-tech databases beyond this specific query.
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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.
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