Agri Comprehensive Management Platform Using AI

Authors: Bhavarth Khairnar, Ganesh Kolhe Pankaj Sonawane, Sanket Malode, Mrs. J.P. Kakad

Country: India

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Abstract: This research paper presents an innovative crop prediction and disease detection system that leverages machine learning techniques to improve agricultural productivity. The proposed system allows farmers to input sensor data to predict crop yields and receive tailored fertilizer recommendations, thereby optimizing resource usage. Through advanced image analysis, the system detects crop diseases and provides actionable insights on suitable pesticides, enhancing crop health management. Additionally, the platform delivers real-time agricultural updates via a news API and offers multi-language support, making it accessible to a diverse user base. A vendor-farmer communication feature is also included, promoting transparent sharing of crop prices and market trends. This comprehensive approach aims to empower farmers with the tools necessary for informed decision-making, ultimately fostering sustainable agricultural practices and improved economic outcomes.

Keywords: Crop Prediction, Disease Detection, Machine Learning, Agricultural Productivity, Sensor Data, Real-Time Updates, Multi-Language Support

Paper Id: 232399

Published On: 2025-04-21

Published In: Volume 13, Issue 2, March-April 2025

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