Deep Learning-Based Agricultural Chatbot with Multi-Language Support for Small Farmers

Deep Learning-Based Agricultural Chatbot with Multi-Language Support for Small Farmers

 

 

YAMINI M

2k21cse186@kiot.ac.in
COMPUTER SCIENCE

AND ENGINEERING

KNOWLEDGE INSTITUTE OF TECHNOLOGY

SALEM, INDIA.

 

SHARMILA S

2k21cse138@kiot.ac.in
COMPUTER SCIENCE AND ENGINEERING

KNOWLEDGE INSTITUTE OF TECHNOLOGY

SALEM, INDIA.

 

SUSHMITHA BA

2k21cse160@kiot.ac.in
COMPUTER SCIENCE

AND ENGINEERING

KNOWLEDGE INSTITUTE

OF TECHNOLOGY

SALEM, INDIA.

 

SWETHA M

2k21cse162@kiot.ac.in
COMPUTER SCIENCE

AND ENGINEERING

KNOWLEDGE INSTITUTE OF TECHNOLOGY

SALEM, INDIA.

Mr. U K BALAJI SARAVANAN B.E, M.E

ukbsces@kiot.ac.in

COMPUTER SCIENCE

AND ENGINEERING

KNOWLEDGE INSTITUTE OF

TECHNOLOGY

SALEM, INDIA.

 

Abstract

Agriculture is an important sector and small-scale farmers typically lack timely and accurate information to increase their productivity. This project presents a Deep Learning Based Agricultural Chatbot with Multi Language Support to assist the small farmers in real time agriculture practice guidance, pest control, weather updates, soil dedication.

Deep learning techniques including Natural Language Processing (NLP) models are used by the chatbot to understand and answer to the farmer queries accurately. This chatbot is multilingual, and the farmer can converse with it in any language, and it mainly relies on pre-trained deep learning models and a huge agricultural knowledge base to give out insights [1][2]. To make the system a reliable virtual assistant for the farmers, extensive datasets are trained to increase response accuracy [3]. This chatbot helps to bridge the knowledge gap in agriculture towards small farmers to provide them with data driven insights that will help them to maximize their yield and manage their risks effectively [4]