Climate-Induced Early Onset of Grape Berry Diseases using ML & IOT

Authors: Pranav Kishor Kachave, Rushikesh Avadhut Patil, Nikita Rajendra Vairal, Sahil Prakash Aher, Prof S.V. Sinha

Country: India

Full-text Research PDF File:   View   |   Download

Abstract: The system combines IoT and Machine Learning technologies to help grape farmers monitor and manage their crops effectively. The system uses IoT sensors like temperature, humidity, and soil moisture sensors, connected to a NodeMCU microcontroller, to continuously track environmental conditions in the vineyard. This data is collected in real-time and provides valuable insights into the growing environment. Additionally, a separate machine learning-based feature allows users to upload photos of grape leaves or plants showing signs of disease. The system analyzes the uploaded images to detect specific grape diseases and provides farmers with accurate disease identification along with actionable prevention measures. By integrating environmental monitoring with advanced disease detection, the system empowers farmers to maintain healthier vineyards, reduce crop loss, and improve overall productivity..

Keywords:

Paper Id: 232558

Published On: 2025-06-05

Published In: Volume 13, Issue 3, May-June 2025

Share this