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Crop diseases are major challenge to agricultural productivity if not detected and managed early. A real-time deep learning-based system for crop disease detection is presented in this work, with subsequent treatment and prevention control measure recommendations. The machine-learning model is essentially based on a custom-trained object detection model developed using a custom dataset. In addition, its usability is further enhanced by location based alerts and multilingual support, ensuring accessibility and relevance across different agricultural areas. The goal is to help farmers to increase productivity, reduce loss, and take early action.

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A Deep Learning-Driven Decision Support System for Real-Time Crop Disease Management

  • 会议论文

  • 发表日期：

    2026年

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  • N. Yuvaraj,
  • Gnanasekaran Thangavel,
  • T. Yugavendhan,
  • S. Vishnuvardhan,
  • D Sindhu Mudaliyar,
  • M. Yoshitha,
  • A. Sharmila

摘要

Crop diseases are major challenge to agricultural productivity if not detected and managed early. A real-time deep learning-based system for crop disease detection is presented in this work, with subsequent treatment and prevention control measure recommendations. The machine-learning model is essentially based on a custom-trained object detection model developed using a custom dataset. In addition, its usability is further enhanced by location based alerts and multilingual support, ensuring accessibility and relevance across different agricultural areas. The goal is to help farmers to increase productivity, reduce loss, and take early action.