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@article{159605,
        author = {Poduri Sri Chiranjeevi Kanaka Bhushnam and Regati Rakesh Reddy and Mallareddy Raja Mouli and Dr. Archana Singh},
        title = {Real-Time Weather Forecasting and Crop Health Monitoring Using an AI-Powered Drone System for Sustainable Agriculture},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {12},
        pages = {233-239},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=159605},
        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.},
        keywords = {Eco-friendly agriculture, AI-driven drone system, Crop health monitoring, Real-time weather prediction, Informed decision-making.},
        month = {},
        }