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Volume 4 Issue 2
March-April 2026
| Author(s) | G. Naveen Kumar, B. Vaishnavi, Ch. Gayathri Bharghavi, K. Shveni |
|---|---|
| Country | India |
| Abstract | The Smart Contract Farming System is a digitalized platform created to connect farmers and buyers more reliably and transparently. Its main goal is to reduce the gap between both buyers and farmers by using secure digitized agreements that clearly define terms and conditions, which helps to build trust and ensures that transactions are fair and well-structured. The platform is developed using Vite and React, through which users can easily register, explore crop listings, view contracts, and interact in real time. On the backend, Node.js and Express.js handle the core application logic, including API services, authentication, contract processing, and transaction management. All data is securely stored and managed using MongoDB, ensuring consistency and reliability. One of the key features of the system is the Price Prediction Module, which works before a contract is finalized. This module uses agricultural datasets collected from IEEE research publications. With the help of Python-based machine learning models, the system predicts crop prices by analyzing historical data, seasonal trends, and market needs and supply. It helps farmers and buyers in making informed decisions and agreeing on fair prices. Once the price is decided, digital contracts are created and accepted by both parties. This system also includes crops based on agricultural seasons such as Kharif, Rabi, and Zaid, which helps in better planning and avoids mismatches between supply and demand. In addition to contract management, the platform involves features like dispute resolution tools and analytical dashboards, which make the overall process more efficient and transparent. Payments are secured through trusted methods such as UPI and escrow systems, ensuring safe and reliable transactions. The feature that makes this application more effective is the Crop Insurance module, which allows farmers to enroll in government-supported insurance schemes. This protects them from unexpected risks like floods, droughts, or pest attacks. Overall, the system is designed to be scalable, efficient, and user-friendly. It strengthens farmers by giving them assured market access while helping buyers get a consistent and trustworthy supply of crops. |
| Keywords | Smart Contract Farming, Machine Learning, Price Prediction, Digital Contracts, React, Node.js, MongoDB, Crop Insurance, UPI Payments, Demand and Supply, Transparency. |
| Discipline | Engineering |
| Published In | Volume 4, Issue 2, March-April 2026 |
| Published On | 2026-04-06 |
| DOI | https://doi.org/10.62127/aijmr.2026.v04i02.1278 |

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