基于人工神经网络的农业助理聊天机器人

N. Chandolikar, Chirag Dale, Tejas Koli, Mayank Singh, Tarussh Narkhede
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引用次数: 2

摘要

由于印度是一个以农业为基础的经济,58%的人口依赖农业作为其主要的生计方式。尽管如此,2019-2020年的经济调查显示,在过去的6年里,印度的农业增长率一直停滞在2.9%左右。考虑到印度仍有许多人依赖它,这确实令人担忧。一个普遍的问题是缺乏正确的信息。这个问题可以通过向农民提供专家建议和相关信息(例如,确定何时灌溉、如何播种以及有效使用哪种杀虫剂来提高产量)来解决。本文提出的聊天机器人AgroBot是一个多用户聊天应用程序。AgroBot可以通过让农民获得在不断变化的市场中取得成功所需的信息,并以易于使用的方式扩大新技术和市场需求,从而克服这一问题。由于系统使用NLP(自然语言处理)来识别和解析农民的查询,识别主要关键词及其问题,识别主要关键词并将其与知识库进行比较,因此农民可以轻松地与聊天机器人进行交流,并提供最佳结果。开发这样一个系统将使农民受益,使他们能够获得有关农业实践的更好信息,从而提高农业生产力。
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Agriculture Assistant Chatbot Using Artificial Neural Network
As India has an agro-based economy, 58% of its population relies on agriculture as its primary method of livelihood. In spite of this, the economic survey for 2019–2020 indicates that agriculture growth in India has stagnated around 2.9% annually for the past 6 years. Considering the number of people in India still relying on it, it is a real concern. One of the prevailing issues is lack of right information. This problem can be solved by providing farmers with expert advice and relevant information (e.g. determine when to irrigate, how to sow seeds, and which pesticides to use effectively to increase the yields). In this paper, the proposed chatbot called AgroBot is a multi-user chat application. AgroBot can overcome this problem by allowing farmers to obtain the information they need to succeed in an ever-changing market and to enlarge with new technology and market demand in an easy-to-use manner. Farmers can communicate easily with the chatbot since the system uses NLP (Natural Language Processing) to identify and parse farmer inquiries, identify the main key words and their questions, identify the main keywords and compare them to the Knowledge Base, and provide the best possible results. The development of such a system would benefit farmers by allowing them to gain better information about agricultural practices and, as a result, increase agricultural productivity.
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