FarmersConnect-Smart Web Application for Direct Agricultural Trade

Abstract

The agricultural sector in India faces significant challenges due to the presence of intermediaries, lack of real-time market information, and limited access to modern technologies for farmers. These issues often result in reduced profits for farmers and inefficient supply chains. To address these challenges, this project proposes FarmersConnect, an AI-powered smart agricultural trade platform that directly connects farmers with buyers, eliminating middlemen and enabling transparent, real-time transactions. The proposed system provides a full-stack digital platform where farmers can list their products, monitor market trends, and interact with buyers seamlessly. The platform incorporates a secure OTP-based authentication system to ensure user safety and accessibility. An integrated AI module utilizing advanced vision models enables automatic crop detection from images, allowing farmers to quickly identify and list their produce with minimal effort. Additionally, real-time price tracking and analytics features help farmers make informed decisions based on current market conditions. Experimental evaluation demonstrates that FarmersConnect improves market accessibility, enhances price transparency, and increases farmer profitability while providing buyers with reliable and direct sourcing options. In conclusion, the platform offers a scalable, efficient, and technology-driven solution that modernizes agricultural trading and strengthens the connection between farmers and consumers.

Introduction

Agriculture is a key part of the Indian economy, but farmers face major challenges in selling their produce due to intermediaries, lack of real-time market data, poor transparency, and limited digital tools. These issues reduce farmer profits and make agricultural trade inefficient. To address this, the proposed system FarmersConnect introduces an AI-powered digital marketplace that directly connects farmers and buyers, eliminating middlemen and improving efficiency.

FarmersConnect uses secure OTP-based authentication and provides separate dashboards for farmers and buyers. It includes an AI-based crop detection system that identifies crops from images and helps farmers list products more easily. The platform also offers real-time price tracking, WebSocket-based live updates, geographic mapping of farmers, direct communication between users, and additional features such as organic product verification, analytics, and an agricultural store.

The literature review highlights the growing use of AI, machine learning, and web-based systems in building intelligent, user-friendly platforms, though many existing solutions still lack full integration of real-time features and adaptive intelligence.

The system architecture follows a multi-layer design including user interface, backend (FastAPI), database (MongoDB), AI modules, and real-time communication using WebSockets. The implementation is divided into four main modules: authentication, product management with AI crop detection, real-time market interaction, and analytics with verification support.

Results show that FarmersConnect significantly improves transparency, efficiency, and usability compared to traditional agricultural trading systems. Farmers benefit from better pricing decisions, reduced manual effort, and increased visibility, while buyers gain easier access to reliable sources and direct communication.

Conclusion

This project presented FarmersConnect, an AI-powered smart agricultural platform designed to improve the efficiency and transparency of agricultural trade by directly connecting farmers and buyers. The system successfully integrates secure authentication, product management, real-time communication, and market price tracking within a unified platform. By enabling farmers to list their products easily and interact directly with buyers, the platform eliminates intermediaries and enhances profitability. The inclusion of AI-based crop detection further simplifies the process of identifying and listing agricultural produce, reducing manual effort and improving accuracy. Additional features such as real-time price updates, location-based farmer discovery, analytics dashboards, and organic product verification contribute to a structured and efficient digital marketplace. The implementation demonstrates that combining modern web technologies with artificial intelligence can significantly improve accessibility, decision-making, and overall user experience in agricultural systems. The overall system proves to be scalable, reliable, and adaptable to different agricultural environments. This work highlights the potential of intelligent digital platforms in transforming traditional farming practices and supporting the growth of technology-driven agriculture.

References

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Copyright

Copyright © 2026 Pirithiswari E, Shree Nithra S, Keerthiga V. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.