Precision Ag Application Quality Control Patent Snapshot
The precision agriculture application quality control patent space is very small and highly concentrated, with 17 patent families on record, dominated by Indian academic and institutional filers. Activity was negligible before 2023 and surged sharply in 2025, suggesting an emerging rather than mature field, though the most recent period should be treated cautiously due to publication lag.
India-anchored academics lead a nascent, highly concentrated field
Vaibhav Laxman Dhasal (Director) holds the top position with 4 patent records, followed by Saveetha Institute of Medical and Technical Sciences with 2 patent records; all remaining ranked applicants hold 1 patent record each.
The top five filers account for 39% of the ranked applicants visible in this query’ combined total, a high concentration ratio for a corpus of this size, indicating that a small cluster of Indian institutions effectively defines the current filing frontier.
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 1 | VAIBHAV LAXMAN DHASAL (DIRECTOR) | 4 | |
| 2 | SAVEETHA INST OF MEDICAL & TECH SCI | 2 | |
| 3 | Dr. D.Y. Patil Institute of Technology, Pimpri, Pune | 1 | |
| 4 | BATTULA NAGA SESHU BABU | 1 | |
| 5 | Lovely Professional University | 1 | |
| 6 | BANDI BALA SUBRAHMANYAM | 1 | |
| 7 | Chandigarh University | 1 | |
| 8 | Dr. D.Y. Patil Institute of Technology, Pimpri, Pune | 1 | |
| 9 | Zhengzhou Tobacco Research Institute of CNTC | 1 | |
| 10 | GUIMARÃES MACHADO FREIRE EDUARDO | 1 |
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 11 | GUIMARÃES MACHADO FREIRE MARCELLO | 1 | |
| 12 | ADEPALLI JAYA SREE | 1 | |
| 13 | DR G N V S L S INDIRA | 1 | |
| 14 | Muthayammal Engineering College | 1 | |
| 15 | GAJJALA VISHNU VARDHAN | 1 | |
| 16 | Nandha Engineering College | 1 | |
| 17 | SAHI VAIDURYA PRATAP | 1 | |
| 18 | Seshadri Rao Gudlavalleru Engineering College | 1 | |
| 19 | Chennai Institute of Technology | 1 |
The visible applicants are academic and engineering-college entities rather than agri-tech corporations or equipment manufacturers, which implies that commercial translation of these inventions remains an open question and that the field is still in its research-publication phase.
Filing activity in 2024 and 2025 is likely under-counted due to standard patent publication lag of 18–24 months; the apparent 2025 surge and 2024 trough should not be interpreted as final figures. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
A sudden 2025 filing surge across AI, soil-work, and business-process branches
Annual filing volume was zero from 2017 through 2022, rose to 2 records in 2023, and reached 14 records in 2025 — the technology composition shows that soil-working, AI-based computing, and image recognition branches are driving that acceleration.
Annual filing trend
Filings were absent for six consecutive years before inflecting in 2023; the 2025 figure of 14 records represents the bulk of the entire corpus. Because publication lag affects the most recent 18–24 months, the 2024 count of 1 and the 2026 count of 0 should not be read as representing final activity levels.
↗ Hover for values · click a bar to ask EurekaTechnology composition
Soil working in agriculture (A01B) and business/admin data processing (G06Q) each appear in 11 patent records, closely followed by AI-based computing (G06N) and image/video recognition (G06V) with 9 each — confirming that the field fuses agronomy with machine-learning and data-management techniques. Lower-frequency branches such as planting and sowing (A01C, 5 records), material analysis (G01N, 2), and digital transmission (H04L, 2) represent adjacent territory that is comparatively sparse.
↗ 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.
Ai assistant for smart farming
The present invention relates to an AI-powered smart farming assistant that integrates a The present invention relates to an AI-powered smart farming assistant that integrates a pocketable external camera with a smartphone to provide real-time soil analysis, crop monitoring, pest detection, and automated farm management. The compact, wireless camera… (excerpt from the patent abstract)
Open this patent in Eureka →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.
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.
Vaibhav Laxman Dhasal (Director)
Leads the corpus with 4 patent records, concentrated in soil working in agriculture (A01B 79), image and video recognition (G06V 20), and AI-based computing (G06N 20). This combination points to a computer-vision-driven approach to field-level application quality control. No momentum data is available for this applicant in the evidence, so trajectory cannot be characterised.
families: 4Saveetha Institute of Medical and Technical Sciences
Holds 2 patent records with a focus on business and admin data processing (G06Q 50), soil working (A01B 79), and planting and sowing (A01C 7) — a broader application-management orientation compared with the leader’s vision-first approach. The institution is flagged as a new entrant in recent filings, indicating freshly initiated activity rather than an established portfolio.
families: 2Frequently asked questions
The corpus contains 17 patent families in scope. This is a very small corpus, indicating an early-stage field with limited established prior art.
Vaibhav Laxman Dhasal (Director) leads with 4 patent records, focused on soil working, image recognition, and AI-based computing methods. The next-ranked filer, Saveetha Institute of Medical and Technical Sciences, holds 2 patent records.
India is visible in with 16 patent records, followed by China with 1 record. No filings appear in the United States, Europe, or other major agricultural markets based on available evidence.
Soil working in agriculture (A01B) and business/admin data processing (G06Q) each appear in 11 patent records, with AI-based computing (G06N) and image/video recognition (G06V) each appearing in 9 records. This indicates the field is built on a fusion of agronomy and machine-learning methods.
No co-applicant relationships are recorded in the evidence. All applicants appear to have filed independently, suggesting fragmented, institution-level research without coordinated industry partnerships.
Material analysis and testing (G01N, 2 records) and drone/UAV platforms (B64C and B64U, 1 record each) are the sparsest branches with plausible technical relevance to application quality control. Digital transmission (H04L, 2 records) and laboratory apparatus (B01L, 1 record) are also comparatively sparse.
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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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