International Journal of Computer Techniques Volume 12 Issue 3 | Detection of Plant Diseases Using AI
Detection of Plant Diseases Using AI
International Journal of Computer Techniques – Volume 12 Issue 3, May – June 2025
Abstract
This study presents an **AI-powered agricultural assistance system** integrating **text-based consultancy, voice interaction, and image-based disease detection** using **deep learning and Retrieval-Augmented Generation (RAG)**. The system employs the **Llama 3.2 3B model**, ensuring **up-to-date agricultural knowledge**, while locally processing queries and images via a CNN model trained on **61,486 plant disease images from 39 categories**.
Keywords
Artificial Intelligence, Plant Disease Detection, Agriculture AI, Deep Learning, Retrieval-Augmented Generation, Machine Learning, CNN, IoT Farming.
Conclusion
The **Smart Agriculture Assistant** integrates **AI-powered consulting and disease detection** to assist farmers with **real-time, customized crop health insights**. Future developments will focus on **multilingual support, offline functionality, and IoT integration for environmental monitoring**, expanding the **scalability and accessibility of AI-driven farming solutions**.
References
- D. Kavitha et al. (2024). “A Smart Agricultural Assistant for Crop Recommendation using Machine Learning.” Grenze International Journal of Engineering and Technology.
- Ayaz et al. (2024). “Revolutionizing Agriculture with Artificial Intelligence: Plant Disease Detection.” Frontiers in Plant Science.
- N. N. H. Nik Hashim et al. (2024). “Artificial Intelligence and IoT-Based Intelligent Farming System for Dragon Fruit Using YOLOv8 Algorithm.” Lecture Notes in Electrical Engineering.
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