Real-Time Weather Forecasting and Crop Health Monitoring Using an AI-Powered Drone System for Sustainable Agriculture
Author(s):
Poduri Sri Chiranjeevi Kanaka Bhushnam, Regati Rakesh Reddy, Mallareddy Raja Mouli, Dr. Archana Singh
Keywords:
Eco-friendly agriculture, AI-driven drone system, Crop health monitoring, Real-time weather prediction, Informed decision-making.
Abstract
The growing urgency for eco-friendly agriculture and precise weather prediction has led to the development of an innovative AI-driven drone system for agricultural monitoring. Combining aerial photography, machine learning, and advanced drone technology, this system delivers real-time insights into crop health and weather patterns. Using the OpenWeatherMap API and machine learning models, the system detects crop health hazards and provides localized forecasts, enabling informed decision-making for resource allocation and crop protection. Preliminary findings showcase the drone system's efficacy and potential to revolutionize precision agriculture with timely, cost-efficient, and environmentally conscious solutions. Future research will focus on refining models, improving data processing efficiency, and exploring adaptability across diverse agricultural contexts.
Article Details
Unique Paper ID: 159605

Publication Volume & Issue: Volume 9, Issue 12

Page(s): 233 - 239
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