MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202521039460 A) filed by Dr. Smita Sudhir Ponde on April 24, 2025, for Modular Ai-Driven Framework For Smart Rural Agriculture: Climate Resilience, Resource Optimization, And Financial Inclusion Scenarios''.
Inventor includes Dr. Smita Sudhir Ponde.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: 7. ABSTRACT OF INVENTION: This invention introduces a modular framework for optimizing smart rural agriculture through a suite of innovative, Al-driven solutions tailored to address the challenges faced by small-scale farmers. The framework comprises six interconnected components, each targeting a specific aspect of agricultural efficiency, resilience, and sustainability. The Adaptive Agro-Climate Fusion Model (AACFM) leverages a hybrid neural network combining convolutional (CNN) and long short-term memory (LSTM) networks to fuse real-time weather data with soil characteristics and crop lifecycle information. This model dynamically predicts weather patterns and provides climate-resilient recommendations to optimize irrigation, pest control, and other farming practices. The Intelligent Agricultural Resource Sharing System (IARSS) integrates blockchain technology with multi-agent reinforcement learning to establish a transparent, cooperative platform for resource sharing. This system enables small-scale farmers to access shared equipment, seeds, and water resources, thereby reducing operational costs and maximizing resource utilization. The Modular Agro-Robotics Framework (MARF) introduces a cost-effective robotic system employing swarm intelligence for field operations on fragmented farmland layouts. These robots, equipped with low-cost sensors, utilize particle swarm optimization for real-time task allocation and adaptability to environmental constraints. The AI-Driven Crop Diversification and Nutritional Mapping (AICDNM) framework uses Bayesian optimization and nutritional mapping to recommend region-specific crop diversification strategies. This approach enhances soil health, aligns crop outputs with regional dietary needs, and increases farmer income sets. The Resilient Disaster Recovery Toolkit (RDRT) integrates predictive analytics and graph neural networks to generate localized recovery plans for agriculture post-disasters, ensuring rapid restoration of farming activities and supply chains. Finally, the Smart Microfinance and Insurance Model (SMIM) uses AI to provide personalized financial support and automated crop insurance claims, improving financial inclusion and reducing economic risks for farmers. This modular framework collectively enhances yield, reduces costs, and improves resilience, representing a transformative approach to rural agriculture optimizations.
Disclaimer: Curated by HT Syndication.
