Smart Agri-Advisor: Integrating Chatbot Technology with CNN-Based Crop Disease Classification for Enhanced Agricultural Decision-Making

Smart Agri-Advisor: Integrating Chatbot Technology with CNN-Based Crop Disease Classification for Enhanced Agricultural Decision-Making
  IJETT-book-cover           
  
© 2024 by IJETT Journal
Volume-72 Issue-7
Year of Publication : 2024
Author : Ratna Patil, Yogita Sinkar, Ashish Ruke, Harshvardhan Kulkarni, Om Kadam
DOI : 10.14445/22315381/IJETT-V72I7P141

How to Cite?

Ratna Patil, Yogita Sinkar, Ashish Ruke, Harshvardhan Kulkarni, Om Kadam, "Smart Agri-Advisor: Integrating Chatbot Technology with CNN-Based Crop Disease Classification for Enhanced Agricultural Decision-Making," International Journal of Engineering Trends and Technology, vol. 72, no. 7, pp. 375-380, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I7P141

Abstract
Smart Agri-Advisor: Integrating Chatbot Technology with CNN-Based Crop Disease Classification for Enhanced Agricultural Decision-Making project presents a comprehensive approach to plant disease classification utilizing a Convolutional Neural Network architecture. Here, the CNN model yields a rather impressive accuracy of 91 percent. Specifically, to identify the disease that is 82% in rate of accuracy in predicting the class of test samples. In turning operation, the loss value is not more than 0. 2238; the CNN model has a stable accuracy to show that the network is useful for real-world applications. Additionally, the system incorporates a chatbot feature developed using React and Natural Language Processing (NLP) techniques, enhancing user interaction and query resolution. Furthermore, a community login/register system powered by MySQL fosters collaboration and knowledge sharing among users. Through seamless integration of machine learning, chatbot technology, and community engagement functionalities, this project offers a holistic solution for plant disease diagnosis and information dissemination within agricultural communities

Keywords
Plant disease classification, Convolutional Neural Network (CNN), Chatbot with NLP, Community engagement, Model performance evaluation.

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