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A Synergistic Integration of IoT, Machine Learning, and Flutter Technology for Precise Crop Management

  • Anirban Chakraborty,
  • Aneesh Bhattacharjee,
  • Harshad Ghadge,
  • Dev Mawley,
  • Aniket Paulzagde,
  • Pravin Jaronde

摘要

This research paper presents “AutoAgro,” a pioneering agricultural framework amalgamating IoT, machine learning, and Flutter technology to revolutionize contemporary farming. Through a network of IoT sensors, real-time environmental parameters vital for agriculture are meticulously captured. Leveraging a sophisticated machine learning model, this data is meticulously analyzed, enabling accurate prediction and early diagnosis of plant diseases. The integration of Flutter technology in our Android interface offers an intuitive platform for farmers, featuring multilingual support and instant disease alerts, fostering proactive management strategies. The paper meticulously details the development, implementation, and performance evaluation of this holistic system, showcasing its potential to optimize crop yield, mitigate losses, and promote sustainable farming practices. Through rigorous experimentation and analysis, this study delves into the transformative impact of intelligent technologies on the agricultural landscape, providing valuable insights for researchers, practitioners, and stakeholders in the field.