Intelligent Agricultural Machine Learning-Based Chatbot Using Python

Abstract

Agriculture remains a cornerstone of India's economy, contributing approximately 20.5% to the national GDP and providing livelihoods to nearly 55% of the population. This marks a substantial rise from its 15.41% contribution in 2018, driven largely by the integration of modern technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Chatbots, and other smart agricultural innovations. In this context, the proposed system introduces a mobile application tailored to support Indian farmers with two core functionalities: a Voice Bot and a Suggestion Bot. The Voice Bot serves as a multilingual agricultural assistant capable of understanding and responding to farmers’ queries in various Indian languages. Developed using tools like the Google Translate API, pyttsx3 for text-to-speech conversion, and real-time search functionalities, it ensures that language barriers do not hinder access to vital agricultural knowledge. Complementing this is the Suggestion Bot, which provides intelligent, data-driven recommendations concerning weather forecasts, optimal crop choices, fertilizer usage, soil health diagnostics, and pest control strategies. By leveraging these features, farmers are empowered to make informed decisions that enhance crop yield, minimize input costs, and promote sustainable farming practices. This holistic approach not only helps in modernizing agriculture but also aligns with national goals of improving rural livelihoods and doubling farmers' incomes. The system exemplifies how technology can bridge the gap between traditional farming methods and digital agriculture, paving the way for a more resilient and prosperous agrarian economy in India.