Krushi Mitra: A Review of Agriculture Bots

Authors

  • Utkarsha Kshirsagar Dept. of Computer Engineering, Vidyalankar Institute of Technology, Mumbai, India
  • Juee Parte Dept. of Computer Engineering, Vidyalankar Institute of Technology, Mumbai, India
  • Mansi Patil Dept. of Computer Engineering, Vidyalankar Institute of Technology, Mumbai, India
  • Amit Aylani Dept. of Computer Engineering, Vidyalankar Institute of Technology, Mumbai, India

DOI:

https://doi.org/10.26438/ijcse/v8i6.4550

Keywords:

Chatbot, Natural Language Processin, (NLP), Agriculture, Prediction Algorithm, Machine Learning

Abstract

India is an agro-based economy and proper information about agricultural practices is an essential key to optimal agricultural growth and output. Artificial Intelligence and Machine Learning are driving the IT industry to a new landscape. In order to answer the queries of the farmer, agricultural Chatbot can be designed. The system “Krushi Mitra” overcomes the problem and provides farmers the better opportunity to obtain the desired information and to scale up with upcoming market trends and technologies in a user friendly manner. Krushi Mitra is actually a chat bot, which is a virtual conversational assistant, through which the users can communicate with the bot as if they are conversing with humans. The focus is on developing the bot in a more intellectual way, that it can even recognize not so well grammatically defined sentences, misspelled words, incomplete phrases, etc. This can help people to converse easily with the bot, since this system uses the Natural Language Processing technique to parse the user queries, identify the keywords, match them with Knowledge Base and respond with the accurate results.

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Published

2020-06-30
CITATION
DOI: 10.26438/ijcse/v8i6.4550
Published: 2020-06-30

How to Cite

[1]
U. Kshirsagar, J. Parte, M. Patil, and Amit Aylani, “Krushi Mitra: A Review of Agriculture Bots”, Int. J. Comp. Sci. Eng., vol. 8, no. 6, pp. 45–51, Jun. 2020.

Issue

Vol. 8 No. 6 (2020): IJCSE June Edition

Section

Review Article

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