AGRIBOT: A Smart AI Companion for Farmers
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Student Project | Computer Technology | India | Volume 14 Issue 4, April 2025 | Popularity: 5 / 10


     

AGRIBOT: A Smart AI Companion for Farmers

Lijo Varghese, Sindhu Daniel


Abstract: Agriculture remains the backbone of many developing economies, yet farmers often face challenges in accessing timely, accurate, and personalized information for effective decision-making. AgriBot is a novel AI-powered chatbot designed to provide real-time agricultural support using machine learning (ML), natural language processing (NLP), and IoT integration. This intelligent system enables farmers to interact through voice or text in multiple languages, offering guidance on crop selection, pest control, soil health, and weather forecasting. The chatbot continuously improves through learning from user interactions, providing precise and region-specific recommendations. With the ability to analyze plant disease images using CNN-based models and suggest appropriate actions, AgriBot enhances farm productivity and sustainability. The system?s cloud-based, scalable design ensures accessibility even in low-connectivity rural areas. This paper presents the architecture, methodology, and implementation of AgriBot and discusses its potential to transform traditional agriculture into a more data-driven and efficient domain.


Keywords: AgriBot, Artificial Intelligence (AI), Natural Language Processing (NLP), Convolutional Neural Network (CNN), Feedforward Neural Network (FNN), Crop Recommendation, Plant Disease Detection


Edition: Volume 14 Issue 4, April 2025


Pages: 1914 - 1918


DOI: https://www.doi.org/10.21275/SR25422192522


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Lijo Varghese, Sindhu Daniel, "AGRIBOT: A Smart AI Companion for Farmers", International Journal of Science and Research (IJSR), Volume 14 Issue 4, April 2025, pp. 1914-1918, https://www.ijsr.net/getabstract.php?paperid=SR25422192522, DOI: https://www.doi.org/10.21275/SR25422192522

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