Farm Digital Twin & Crop Model Patent Landscape 2026
The farm digital twin and crop model patent field is in a confirmed growth stage, with filings expanding roughly 800% over the review window and Indian academic institutions dominating all top filing positions. Activity is heavily concentrated in India, and the competitive structure is defined by universities rather than agri-tech corporates or equipment manufacturers.
Indian universities lead a field with limited corporate participation
Lovely Professional University holds the top position with 13 patent families, followed closely by CVR College of Engineering with 12 and Chandigarh University with 11. Every applicant in the top twenty is an Indian academic or research institution, or an individual inventor — no global agri-tech corporation or precision-agriculture OEM appears in the ranked list.
The top five filers account for 21% of the combined output of the hundred largest filers, indicating a moderately diffuse field at the top tier with no single dominant assignee commanding a commanding lead. The gap between the leader (13 patent families) and the twentieth-ranked applicant (3 patent families) is narrow, reinforcing the fragmented structure.
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 1 | Lovely Professional University | 13 | |
| 2 | CVR College of Engineering | 12 | |
| 3 | Chandigarh University | 11 | |
| 4 | SAVEETHA INST OF MEDICAL & TECH SCI | 9 | |
| 5 | SR University | 9 | |
| 6 | Manipal University Jaipur | 8 | |
| 7 | Vaibhav Laxman Dhasal (Director) | 6 | |
| 8 | KKR & KSR INST OF TECH & SCI | 6 | |
| 9 | Dayananda Sagar College of Engineering | 4 | |
| 10 | Anurag University | 4 |
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 11 | JIS College of Engineering | 4 | |
| 12 | REVA University | 4 | |
| 13 | Koneru Lakshmaiah Education Foundation | 3 | |
| 14 | Dr. Sandip Debnath | 3 | |
| 15 | Sona College of Technology | 3 | |
| 16 | N. Gopinath | 3 | |
| 17 | Saveetha Engineering College | 3 | |
| 18 | Narula Institute of Technology | 3 | |
| 19 | Dr. Rajesh Bhaskar Survase | 3 | |
| 20 | Dattatray G. Takale | 3 |
This university-led structure implies that the foundational IP layer for farm digital twins is being built primarily as applied research output rather than as commercial product IP. For a corporate entrant, the competitive barrier from existing patent positions is relatively low, but the technology base is being established quickly and the window for staking core claims is narrowing.
Filings from the most recent 18–24 months are likely under-represented due to standard patent publication lag; the true volume for 2025 and 2026 will be higher than current counts suggest. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Rapid volume growth paired with a software-and-AI-heavy technology mix
Two structural patterns define this field: an accelerating annual filing trajectory driven almost entirely by Indian academic institutions, and a technology composition dominated by business data processing and AI rather than field-level agricultural hardware.
Annual filing trend
Filings were negligible through 2020 (single digits annually), then stepped up sharply from 2021 onward — 10 families in 2021, 35 in 2023, 111 in 2024, and 196 in 2025. The 2026 figure of 100 families covers only part of the year and will rise significantly as publications catch up. The overall growth rate across the review window is approximately 800%, consistent with the Growth lifecycle stage.
↗ Hover for values · click a bar to ask EurekaTechnology composition
The dominant IPC branch is G06Q (business and administrative data processing), reflecting system-level farm management architectures. G06N (AI computing models) ranks second, followed by A01B (soil working in agriculture) and A01G (horticulture and forestry). Digital communications (H04L) and materials analysis (G01N) round out the mid-tier. The skew toward software and AI classes over core agricultural mechanization classes suggests the field is primarily developing decision-support and simulation layers rather than embedded hardware control.
↗ 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.
Mini drone and agbot based distributed system and …
In this invention a Web Server based distributed cellular system to provide 21st century total digital precision agriculture to small and uneducated poor farmers is proposed. A service model is used to avoid farmers owning any equipment and a system’s provided service agent becomes on ground mentor of the farmer. The invention uses plurality of low cost… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Precision agriculture system and related methods | 38 |
| 2 | Smart farming | 13 |
| 3 | Crop- prediction: intelligent prediction of crop w… | 10 |
| 4 | Mini drone and agbot based distributed system and … | 9 |
| 5 | Smart decision support system architecture for IoT… | 9 |
| 6 | 一种基于多源数据的作物估产方法 | 4 |
| 7 | Smart farming | 4 |
| 8 | Soil fertility evaluation and management | 3 |
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
The combination of a growth-stage lifecycle, university-dominated filing base, and near-total geographic concentration in India creates a distinctive risk-opportunity profile for corporate and institutional R&D planners.
Early Growth — core IP layer still being formed
The lifecycle assessment places this field firmly in Growth, with annual filing volume still rising and the multi-year window showing approximately 800% expansion. The field moved from near-zero activity before 2019 to triple-digit annual filings by 2024, meaning core architectural patents are still being filed. An entrant today would be competing in an active formative period rather than entering a mature, crowded space.
Growth stageFragmented top tier with no dominant corporate assignee
The top five filers hold 21% of the combined output of the hundred largest filers, and the lead applicant holds only 13 patent families. All top-ranked filers are Indian academic institutions or individual inventors. This means the field lacks the type of large-portfolio corporate blockades common in mature agri-tech segments, but also that licensed or transferable technology clusters are currently thin.
FragmentedNo recorded co-applicant activity in the evidence base
Collaboration data returns no co-filing relationships in the current evidence set. This is consistent with the individual-university filing model observed in the applicant ranking, where each institution files independently. The absence of cross-institution or industry-academia co-filing suggests that collaborative R&D consortia — common in hardware-intensive agri-tech — have not yet formed around digital twin and crop-model IP in this corpus.
Evidence pendingIndia-centric with minimal international coverage
India accounts for the overwhelming majority of patent records in this corpus, with the United States at 4 records, WIPO PCT at 2, China at 1, and the United Kingdom at 1. This concentration means most of the existing IP offers limited direct competitive threat outside India, but also that international filing coverage for farm digital twin technologies remains nearly open. Organizations seeking broad geographic protection for innovations in this space face minimal blocking positions in the US, Europe, or China.
India-dominantGo 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.
Top filers emphasize AI-enabled farm management systems over hardware
The leading applicants share a common technology emphasis centered on AI computing models and agricultural data processing, with most entering the ranking as new entrants in the most recent filing period — indicating the competitive field assembled rapidly.
Lovely Professional University
The top-ranked filer with 13 patent families, Lovely Professional University entered the ranking as a new entrant in the recent period, with 7 recent-period families. Its technology focus spans soil working in agriculture (A01B), business data processing (G06Q), and AI computing models (G06N) — a broad platform covering both agronomic inputs and the analytical layer above them.
families: 13CVR College of Engineering
CVR College of Engineering ranks second with 12 patent families and is also a new entrant in momentum terms, with 3 recent-period families. Its strongest IPC concentration is in business and administrative data processing (G06Q) with 11 records, complemented by soil working (A01B) and AI models (G06N). The near-parity with the leader and new-entrant momentum signal that it is actively building its position rather than coasting on prior filings.
families: 12| Applicant | Recent (3 yrs) | Trend |
|---|---|---|
| Lovely Professional University | 7 | ▲ new entrant |
| CVR College of Engineering | 3 | ▲ new entrant |
| Chandigarh University | 2 | ▲ new entrant |
| SAVEETHA INST OF MEDICAL & TECH SCI | 7 | ▲ new entrant |
| Manipal University Jaipur | 3 | ▲ new entrant |
| KKR & KSR INST OF TECH & SCI | 2 | ▲ new entrant |
| REVA University | 1 | ▲ new entrant |
| KRISHAN KUMAR | 4 | ▲ new entrant |
Under-served branches adjacent to the dominant AI and agronomy core
Several IPC branches appear in the technology composition at relatively low share levels despite having direct technical relevance to farm digital twin architectures — these are observations of relative sparsity, not validated commercial opportunities.
G06V · Image and Video Recognition for Crop Monitoring
G06V accounts for 64 patent records — a 4% share among the branches observed — despite image and video recognition being a foundational input layer for crop condition assessment, disease detection, and yield estimation in digital twin pipelines. The branch is technically adjacent to the dominant AI (G06N) and horticulture (A01G) classes already active in the field. A realistic entry path exists for teams combining drone or satellite imagery with crop-model inference, particularly given the separate presence of B64C (aeroplanes and helicopters, 29 records) and B64U (unmanned aerial vehicles, 7 records) in the composition.
Search this in Eureka →G01W · Meteorology and Weather Integration
G01W (meteorology) appears with only 11 patent records, making it one of the sparsest branches in a corpus where weather-driven crop modeling is a core use case. Microclimate and forecast data integration is a standard component of commercial crop simulation platforms, yet the IP footprint here is minimal. For teams building physics-based or hybrid crop models that ingest real-time and forecast weather data, this branch represents a sparse area with plausible technical value and a direct connection to the dominant G06Q and G06N classes already well-represented in the field.
Search this in Eureka →How leading institutions differ by technology route emphasis
Route coverage across the main technology branches in the current evidence set.
| Player | G06Q 50 · Business, commerce & admin data processing | A01B 79 · Soil working in agriculture | G06N 20 · Computing based on AI models | A01G 25 · Horticulture & forestry | G06Q 10 · Business, commerce & admin data processing |
|---|---|---|---|---|---|
| Chandigarh University | Strong · 9 | Strong · 5 | Strong · 7 | Strong · 8 | Moderate · 2 |
| CVR College of Engineering | Strong · 11 | Strong · 6 | Moderate · 4 | Absent | Moderate · 4 |
| Saveetha Institute of Medical and Technical Sciences | Strong · 9 | Strong · 6 | Absent | Strong · 5 | Moderate · 4 |
| Lovely Professional University | Strong · 9 | Strong · 9 | Strong · 5 | Absent | Absent |
| Manipal University Jaipur | Strong · 6 | Strong · 7 | Strong · 4 | Absent | Moderate · 3 |
| SR University | Strong · 9 | Moderate · 3 | Strong · 5 | Absent | Absent |
| Anurag University | Strong · 4 | Strong · 3 | Absent | Moderate · 2 | Moderate · 2 |
Frequently asked questions
The current evidence covers 477 patent families in scope globally, with filings dating back to 2017 and accelerating sharply from 2021 onward. The most recent 18–24 months will show higher final counts once publication lag resolves.
Lovely Professional University leads with 13 patent families, followed by CVR College of Engineering with 12 and Chandigarh University with 11. All top-ranked filers are Indian academic institutions or individual inventors.
The field is assessed as being in the Growth stage, with annual filings still rising and an approximately 800% expansion recorded across the review window. This indicates the foundational IP layer is still being actively formed.
India accounts for the overwhelming majority of patent records in this corpus. The United States, WIPO PCT, China, and the United Kingdom each contribute only a small number of records, meaning international filing coverage outside India is currently sparse.
Business and administrative data processing (G06Q) is the largest single class, followed by AI computing models (G06N), soil working in agriculture (A01B), and horticulture and forestry (A01G). This mix reflects a software and decision-support emphasis rather than embedded hardware control.
Image and video recognition (G06V) and meteorology (G01W) are both technically relevant to crop modeling yet appear at relatively low share in the current composition — 4% and under 1% respectively. These are observations of relative sparsity; teams with capabilities in visual crop assessment or weather-integrated simulation may find less crowded IP territory in these branches.
Built on Patsnap Open Platform
This report’s underlying patent dataset — filings, assignees, technology clusters — is open for developers via MCP and REST API. Free to start, 10,000 credits, no credit card required.
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.