MUMBAI, India, Jan. 9 -- Intellectual Property India has published a patent application (202541112305 A) filed by New Prince Shri Bhavani College Of Engineering And Technology; Jenovas D A; Rishabanandan J; Nalayiramuthupandian B; Sanjay Raj R; and Dr. Ahila R, Chennai, Tamil Nadu, on Nov. 17, 2025, for 'smart subsidy recommender for local farmers using genai and geodb.'
Inventor(s) include Jenovasda; Rishabanandan J; Nalayiramuthupandian B; Sanjayraj R; and Dr. Ahila R.
The application for the patent was published on Jan. 9, under issue no. 02/2026.
According to the abstract released by the Intellectual Property India: "The invention provides a Smart Subsidy Recommender for Farmers that integrates Generative Artificial Intelligence (GenAI) with geospatial databases (GeoDB + PostGIS) to deliver customized access to government schemes and subsidy programs. Unlike conventional platforms that display generalized lists, this system intelligently adapts to the individual farmer's profile, which includes land size, cropping history, irrigation techniques, and precise geographic location. Using LangChain-powered natural language processing, the system interprets farmer queries expressed in their preferred language and matches them with suitable subsidy options. The core architecture consists of a FastAPI backend, which manages communication between the Al reasoning engine and the relational database, supported by a PostgreSQL database with PostGIS extensions for geospatial filtering and analysis. A React or Streamlit frontend ensures accessibility through an intuitive design and offers multilingual interaction, enabling inclusion of fanners across diverse regions and literacy levels. In addition to personalized recommendations, the system maintains an administrative dashboard that allows authorized personnel to update schemes, monitor usage, and optimize subsidy distribution. The recommender robotically processes query interpretation, spatial validation, and scheme matching in real time, presenting results tailored to both the farmer's contextual needs and the regulatory framework of their location. Its modular design includes: 1. User registration and profile management; 2. Al-powered query understanding and contextual reasoning; 3. Spatial filtering and mapping through GeoDB/PostGIS; 4. Recommendation engine for subsidy selection; 5. Multilingual communication layer; and 6. Administrative control and reporting tools. The invention offers significant benefits by increasing awareness of government schemes, bridging the gap between policy and beneficiaries, and promoting agricultural sustain ability. It also enhances financial inclusion, ensures more effective utilization of subsidies, and reduces dependency on manual advisory channels. By uniting real-time Al-driven recommendations, geospatial analytics, and multilingual accessibility, this system represents a novel, scalable, and socially impactful innovation in the domain of digital agriculture and rural development."
Disclaimer: Curated by HT Syndication.
