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1. Team Details Team name: Logic Loom Team leader name: Rohan Singh V Problem Statement: Empowering Small And Marginal Farmers with AI Driven Agricultural Solutions.

2. Brief about your solution The Smart Agri-Tech Platform integrates IoT, AI, and blockchain to support small and marginal farmers. IoT sensors monitor soil and weather conditions in real-time, enabling informed decision-making. AI optimizes irrigation, fertilization, and pest control, reducing resource waste. A cloud-based marketplace connects farmers directly with buyers, ensuring fair pricing and eliminating middlemen. Digital financial services offer microloans, subsidies, and weather-based crop insurance to mitigate financial risks. AI-driven advisory services provide real-time guidance on best farming practices, boosting productivity and sustainability.

3. Opportunities How different is it from any of the other existing ideas? Integrates IoT , AI, and blockchain into a unified system for small and marginal farmers. Offers a holistic approach, combining real-time soil/weather monitoring, precision farming, and a blockchain marketplace. Includes financial services like microloans, crop insurance, and AI-powered advisory support. How will it be able to solve the problem? Provides data-driven decision-making to optimize irrigation, fertilization, and pest control. Blockchain marketplace eliminates middlemen and ensures fair pricing. Financial services safeguard farmers against economic risks, while AI advisory enhances productivity and knowledge. USP of the proposed solution Comprehensive, end-to-end solution with IoT , AI, and blockchain . Optimizes farming practices and resources through real-time AI-driven decision-making. Ensures direct transactions with fair pricing via a blockchain marketplace. Promotes financial inclusion through microloans, subsidies, and insurance. AI-powered guidance boosts productivity and supports sustainable, eco-friendly farming.

4. List of features offered by the solution Real-Time Monitoring Soil moisture, temperature, and nutrient levels. Crop health and growth status. Automated Irrigation Systems Smart irrigation scheduling based on real-time data. Water usage optimization. Aerial Surveillance Drone-based crop monitoring for early detection of issues. High-resolution imaging for detailed analysis. Precision Farming Tools Satellite imagery for field mapping and analysis. Variable rate application of inputs (fertilizers, pesticides). Predictive Analytics Weather forecasts and climate impact predictions. Pest and disease outbreak predictions.

5. Mobile Applications User-friendly interface for accessing farming insights. Alerts and notifications for critical farming activities. Supply Chain Management Blockchain for traceability and transparency. Secure transactions and access to markets. Community and Knowledge Sharing Platforms for farmers to share experiences and advice. Access to expert consultations and resources. Financial Services Access Tools for budgeting and financial planning. Connections to microloans and insurance options.

6. Process flow diagram or Use-case diagram

7. Architecture diagram of the proposed solution

8. Technologies to be used in the solution Artificial Intelligence (AI) & Machine Learning (ML) Predictive Analytics: Custom AI models analyze historical weather, soil, and crop data to provide forecasts for optimal sowing, irrigation, and harvesting. Pest & Disease Detection: AI-powered image recognition helps identify crop diseases and suggests remedies using mobile phone cameras. Yield Prediction: ML models predict crop yield based on soil health, weather conditions, and farming practices. 2. Internet of Things (IoT) & Smart Sensors Soil & Weather Sensors: Soil NPK Sensors and other sensors to monitor soil moisture, temperature, pH, and weather conditions in real time, providing actionable insights. Automated Irrigation Systems: IoT-enabled drip irrigation optimizes water usage based on real-time soil moisture levels.

9. 3. Blockchain Technology Traceability & Food Safety: Consumers and retailers can trace the origin of food products, ensuring quality and fair trade. 4. Mobile & Cloud-Based Solutions AI-Powered Advisory App: A mobile app provides farmers with real-time farming recommendations in their local language. Cloud-Based Data Storage: Secure storage of weather, soil, and market data for better decision-making. Remote Crop Monitoring: Farmers can track farm conditions using a smartphone, reducing the need for frequent field visits.

10. 1. Geospatial Technology (GIS & Remote Sensing) AI-powered satellite and drone imagery helps monitor crop health, soil fertility, and pests. GIS maps and drone surveys optimize farming zones for maximum productivity. 2. Big Data & Analytics AI analyzes market trends for crop price forecasting and weather data for hyperlocal climate alerts, preventing distress sales and improving decision-making. 3. Edge Computing & 5G Connectivity AI models on edge devices enable real-time data processing in remote areas. 5G connectivity ensures fast, reliable data transmission for IoT sensors and AI applications.

11. Snapshots of the MVP

12. Snapshots of the MVP