AI-Driven Plant Disease Diagnosis with Conversational Chatbot Support for Precision Farming
| International Journal of Electronics and Communication Engineering |
| © 2025 by SSRG - IJECE Journal |
| Volume 12 Issue 10 |
| Year of Publication : 2025 |
| Authors : Raja Rajeshwari M, Swapna B, Anand M |
10.14445/23488549/IJECE-V12I10P103
How to Cite?
Raja Rajeshwari M, Swapna B, Anand M, "AI-Driven Plant Disease Diagnosis with Conversational Chatbot Support for Precision Farming," SSRG International Journal of Electronics and Communication Engineering, vol. 12, no. 10, pp. 15-26, 2025. Crossref, https://doi.org/10.14445/23488549/IJECE-V12I10P103
Abstract:
Agricultural productivity remains extremely vulnerable due to a lack of plant disease detection. This stage leads to a drastic disaster in crop productivity, which significantly affects food prosperity globally and affects farmers’ ability to manage their agricultural systems. Early plant disease detection improves the agricultural management system, and providing the best practices in an applicable way leads to faster, sustainable farming practices. The proposed technique leverages AI Models to analyze plant leaf images and accurately describe the diseases affected, while a Natural Language Processing (NLP)-based chatbot delivers valid actionable insights and treatment recommendations to farmers for fast recovery of the plant in their own multilingual language. This technique provides high accuracy in maintaining the latency level. This framework offers chatbot assistance for farmers to guide the best agricultural practices, especially treating disease-affected plants, to promote their crop production. Additionally, the system provides the integration of a multilingual chatbot to help farmers in their native language.
Keywords:
Plant Disease Detection, Precision Agriculture, Chatbot Integration, Deep Learning, Sustainable Farming.
References:
[1] Aanis Ahmad, Dharmendra Saraswat, and Aly El Gamal, “A Survey on using Deep Learning Techniques for Plant Disease Diagnosis and Recommendations for Development of Appropriate Tools,” Smart Agricultural Technology, vol. 3, pp. 1-13, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Imtiaz Ahmed, and Pramod Kumar Yadav, “Plant Disease Detection using Machine Learning Approaches,” Expert Systems, vol. 40, no. 5, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Ishana Attri, Lalit Kumar Awasthi, and Teek Parval Sharma, “Machine Learning in Agriculture: A Review of Crop Management Applications,” Multimedia Tools and Applications, vol. 83, pp. 12875-12915, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Wubetu Barud Demilie, “Plant Disease Detection and Classification Techniques: A Comparative Study of the Performances,” Journal of Big Data, vol. 11, pp. 1-43, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Sunil S. Harakannanavar et al., “Plant Leaf Disease Detection using Computer Vision and Machine Learning Algorithms,” Global Transitions Proceedings, vol. 3, no. 1, pp. 305-310, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Langning Huo et al., “Assessing the Detectability of European Spruce Bark Beetle Green Attack in Multispectral Drone Images with High Spatial-and Temporal Resolutions,” Remote Sensing of Environment, vol. 287, pp. 1-17, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[7] C. Jackulin, and S. Murugavalli, “A Comprehensive Review on Detection of Plant Disease Using Machine Learning and Deep Learning Approaches,” Measurement: Sensors, vol. 24, pp. 1-10, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Johnson Kolluri, Sandeep Kumar Dash, and Ranjita Das, “Plant Disease Identification Based on Multimodal Learning,” International Journal of Intelligent Systems and Applications in Engineering, vol. 12, no. 15S, pp. 634-643, 2024.
[Google Scholar] [Publisher Link]
[9] Sonali Kothari et al., “CropGuard: Empowering Agriculture with AI-driven Plant Disease Detection Chatbot,” International Journal of Intelligent Systems and Applications in Engineering, vol. 12, no. 12S, pp. 530-537, 2024.
[Google Scholar] [Publisher Link]
[10] Lili Li, Shujuan Zhang, and Bin Wang, “Plant Disease Detection and Classification by Deep Learning-A Review,” IEEE Access, vol. 9, pp. 56683-56698, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Houda Orchi, Mohamed Sadik, and Mohammed Khaldoun, “On Using Artificial Intelligence and the Internet of Things for Crop Disease Detection: A Contemporary Survey,” Agriculture, vol. 12, no. 1, pp. 1-29, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Adesh V. Panchal et al., “Image-Based Plant Diseases Detection Using Deep Learning,” Materials Today: Proceedings, vol. 80, no. 3, pp. 3500-3506, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[13] S.R. Prasad, and G.S. Thyagaraju, “Leaf Analysis-Based Early Plant Disease Detection Using Internet of Things, Machine Learning and Deep Learning: A Comprehensive Review,” Journal of Integrated Science and Technology, vol. 12, no. 2, pp. 1-14, 2024.
[Google Scholar] [Publisher Link]
[14] Pratik Prasad Singh et al., “Deep Learning Techniques for Plant Disease Detection and Classification: A Comprehensive Review,” International Journal of Advanced Biochemistry Research, vol. 9, no. 1S, pp. 187-200, 2025.
[CrossRef] [Publisher Link]
[15] Rohan Kumar Raman et al., “Reconnoitering Precision Agriculture and Resource Management: A Comprehensive Review from an Extension Standpoint on Artificial Intelligence and Machine Learning,” Indian Research Journal of Extension Education, vol. 24, no. 1, pp. 108-123, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Saurav Sagar, Mohammed Javed, and David S Doermann, “Leaf-Based Plant Disease Detection and Explainable AI,” arXiv Preprint, pp. 1-14, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[17] P. Sajitha et al., “A Review on Machine Learning and Deep Learning Image-Based Plant Disease Classification for Industrial Farming Systems,” Journal of Industrial Information Integration, vol. 38, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Chittabarni Sarkar et al., “Leaf Disease Detection using Machine Learning and Deep Learning: Review and Challenges,” Applied Soft Computing, vol. 145, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Rahul Sharma et al., “Plant Disease Diagnosis and Image Classification Using Deep Learning,” Computers, Materials & Continua, vol. 71, no. 2, pp. 2125-2140, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[20] S.A. Sivakumar et al., “Artificial Intelligence-Based Agricultural Chatbot and Virtual Assistant for Delivery of Harvested Crops,” International Journal of Intelligent Systems and Applications in Engineering, vol. 11, no. 8S, pp. 576-583, 2023.
[Google Scholar] [Publisher Link]
[21] Santosh Kumar Upadhyay, and Avadhesh Kumar, “A Novel Approach for Rice Plant Diseases Classification with Deep Convolutional Neural Network,” International Journal of Information Technology, vol. 14, pp. 185-199, 2022.
[CrossRef] [Google Scholar] [Publisher Link]