Authors :
K. Venkat Reddy; E. Sathvik; K. Laya; K.S.K. Sri Harsha
Volume/Issue :
Volume 9 - 2024, Issue 5 - May
Google Scholar :
https://tinyurl.com/59ks3nnc
Scribd :
https://tinyurl.com/yeyf7dpr
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAY180
Abstract :
Nowadays, every sector is developing in its
own way, except the agriculture sector. The main goal of
the project is to develop the agriculture sector and give
hope to the farmers to grow themselves. In our opinion,
in the future there will be no farmers, so this project
may have an impact on agriculture. The chatbot will
help humans gain more knowledge about the different
aspects of good agriculture. We have designed this
project using some ML techniques, AI, and NLP. The
main results of this project will be about crop
management, such as fertilizer dosage and nutrient
requirements. The key strength of the chatbot lies in its
integration with authoritative sources from "The Indian
Council of Agricultural Research" (ICAR). Overall, this
project mainly gives results about how good agriculture
can be done.
Keywords :
Natural Language Processing (NLP), Disease Detection, Machine Learning, Chatbot, Crop Management.
References :
- An AI-Based Chatbot Using Deep Learning." In Intelligent Systems, pp. 231-242.AppleAcademic Press,2019.
- J. Vijayalakshmi, K. PandiMeena, “Agriculture TalkBot Using AI”, International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277 – 3878, Volume-8, Issue-2S5, July 2019.
- J. Bang, H. Noh, Y. Kim and G. G. Lee, "Example-based chat-oriented dialogue system with personalized long-term memory", 2015 International Conference on Big Data and Smart Computing (BIGCOMP), Jeju, 2015.
- E. Haller and T. Rebedea, "Designing a Chat-bot that Simulates an Historical Figure," 2013 19th International Conference on Control Systems and Computer Science, Bucharest, 2013.
- S. J. du Preez, M. Lall and S. Sinha, "An intelligent web-based voice chat bot," EUROCON 2009, EUROCON '09. IEEE, St.-Petersburg, 2009. [6] Y. Chen, W. Wang and Z. Liu, "Keyword based search and exploration on databases," 2011 IEEE 27th International Conference on Data Engineering, Hannover, 2011.
- B. K. Kim, J. Roh, S. Y. Dong, and S. Y. Lee, “Hierarchical committee of deep convolutional neural networks for robust facial expression recognition,” Journal on Multimodal User Interfaces, pp. 1-17, 2016.
- L. Chao, J. Tao, M. Yang, Y. Li, and Z. Wen, “Audio Visual Emotion Recognition with Temporal Alignment and Perception Attention,” arXiv preprint arXiv:1603.08321, 2016.
- H. Lee, Y. S. Choi, S. Lee, and I. P. Park, “Towards unobtrusive emotion recognition for affective social communication,” In proc. Of 2012 IEEE Consumer Communications and Networking Conference, pp. 260-264, 2012.
- M. Wollmer, F. Weninger, T. Knaup, B. Schuller, C. Sun, K. Sagae, and L. P. Morency, “youtube movie reviews: Sentiment analysis in an audio-visual context,” IEEE Intelligent Systems 28(3), pp. 46-53, 2013.
- A. Hommersom, P. J. Lucas, M. Velikova, G. Dal, J. Bastos, J. Rodriguez, M. Germs, and H. Schwietert, “Moshca-my mobile and smart healthcare assistant,” In proc. of e-Health Networking, Applications & Services (Healthcom), pp. 188-192, 2013.
- R. J. Vidmar. (1992, August). On the use of atmospheric plasmas as electromagnetic reflectors. IEEE Trans. Plasma Sci. [Online].
Nowadays, every sector is developing in its
own way, except the agriculture sector. The main goal of
the project is to develop the agriculture sector and give
hope to the farmers to grow themselves. In our opinion,
in the future there will be no farmers, so this project
may have an impact on agriculture. The chatbot will
help humans gain more knowledge about the different
aspects of good agriculture. We have designed this
project using some ML techniques, AI, and NLP. The
main results of this project will be about crop
management, such as fertilizer dosage and nutrient
requirements. The key strength of the chatbot lies in its
integration with authoritative sources from "The Indian
Council of Agricultural Research" (ICAR). Overall, this
project mainly gives results about how good agriculture
can be done.
Keywords :
Natural Language Processing (NLP), Disease Detection, Machine Learning, Chatbot, Crop Management.