Smart Farming: A Web-based Approach using ML

Farming is the backbone of India's economy, yet those involved in the industry are predominantly from lower socioeconomic backgrounds and suffer from poverty. Recognizing the need for an effective advisory support system for small-scale farmers, the ‘Farmer Support System’ has been developed This web-based project provides farmers with access to essential information and resources to aid in their agricultural practices. In this paper, the researchers describe the various features incorporated into the system. To develop a web based farmer support system, Node, Express.js and Flask have been utilized as back-end tools, and HTML, CSS, EJS view engine, and JavaScript are used for front-end development. The system retrieves data through communication with two Python dictionaries that hold information on crops and fertilizers. Unlike many current recommendation systems, such as “Crop Prediction using Machine Learning” by Kalimuthu, M, P. Vaishnavi, and M. Kishore (2020), the proposed application not only predicts the most suitable crop for a farmer's plot, but also provides detailed guidance on the cultivation process. The system also allows users to search for information on any crop, predict the most appropriate fertilizer for their farm and provides real-time chat support to address any queries they may have. By offering comprehensive guidance on nearly every aspect of crop cultivation, this application aims to increase overall productivity for farmers.