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ISSN Approved Journal || eISSN: 2582-8185 || CODEN: IJSRO2 || Impact Factor 8.2 || Google Scholar and CrossRef Indexed

Peer Reviewed and Referred Journal || Free Certificate of Publication

Research and review articles are invited for publication in March 2026 (Volume 18, Issue 3) Submit manuscript

FarmTechBot (FTB): Empowering farmers for better harvest

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  • FarmTechBot (FTB): Empowering farmers for better harvest

G. Kalaiselvi 1, *, B. Rubavarshini 2, T. Thirumullai 2 and I. Dhivyadharshini 2

1 Assistant Professor, Department of Computer Science and Engineering, Anjalai Ammal Mahalingam Engineering College, Kovilvenni, Tamil Nadu, India.
2 UG Student, Department of Computer Science and Engineering, Anjalai Ammal Mahalingam Engineering College, Kovilvenni, Tamil Nadu, India.

Review Article
 
International Journal of Science and Research Archive, 2024, 12(01), 055-062.
Article DOI: 10.30574/ijsra.2024.12.1.0758
DOI url: https://doi.org/10.30574/ijsra.2024.12.1.0758

Received on 18 March 2024; revised on 27 April 2024; accepted on 29 April 2024

In an evolving world, the FarmTechBot (FTB) emerges as a pioneering digital assistant, empowering farmers with essential insights and real-time information crucial for optimizing agricultural practices. The presence of chatbot functionality capable of addressing queries related to soil, pest, and market linkage associates to overcome hurdles for users seeking real-time information. Furthermore, the lack of voice recognition capabilities limits accessibility, especially for users who prefer or require voice-based interaction. Additionally, the manual process of pest identification from uploaded crop images hampers efficiency, prolonging the time required for pest management. The FTB represents a significant advancement in agricultural technology, addressing the existing system's limitations and empowering farmers with real-time information, enhanced accessibility, and streamlined pest management capabilities. The FTB utilizes a combination of techniques including Histogram of Oriented Gradients (HOG) for image feature extraction and classification using Support Vector Classifier (SVC). In Natural Language Processing (NLP), it employs tokenization and TF-IDF vectorization for text preprocessing and representation, alongside Linear Support Vector Classifier (LinearSVC) for intent classification.

Chatbot; Natural Language Processing; Agriculture; Support Vector Classifier

https://ijsra.net/sites/default/files/fulltext_pdf/IJSRA-2024-0758.pdf

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G. Kalaiselvi, B. Rubavarshini, T. Thirumullai and I. Dhivyadharshini. FarmTechBot (FTB): Empowering farmers for better harvest. International Journal of Science and Research Archive, 2024, 12(01), 055-062. Article DOI: https://doi.org/10.30574/ijsra.2024.12.1.0758

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


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