A study of conversational agent solution technologies for banana farmer assistance

Luis-Alexander Calvo-Valverde, None Kevin Rojas-Salazar, None Jose Fabio Hidalgo-Rodríguez, None Versalio Mora, None Jorge A. Sandoval, None Erick Bolaños-Céspedes, None Carlos Quirós
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Abstract

Modern agricultural extension services help as a source of information for farmer queries. One of its applications are local hot lines where expert agents in specific crops or fields assist in farmer agricultural practices and decisions. As an already established technology in the field of customer services, conversational agents can help this solution by covering for experts when users have difficulties contacting them. These artificial agents can answer general queries at any hour, increasing the extension service accessibility. The creation of a contextualized solution is possible with the advancements of Natural Language Processing (NLP) and its accessibility in cloud services. We write this paper to collect state-of-the-art research on agricultural conversational agents and tools used for its design and deployment. General knowledge on current applications is gather and can later be used to help in the design of a localized solution when agricultural services are difficult to access. Lastly, we describe and analyze a chatbot prototype in the specific field of banana farming using IBM Watson services and the messaging platform Telegram App.
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香蕉种植户援助的对话代理解决方案技术研究
现代农业推广服务作为农民查询的信息来源。它的应用之一是当地热线,由特定作物或田地的专家代理协助农民的农业实践和决策。作为客户服务领域的一项成熟技术,会话代理可以在用户联系专家有困难时代替专家,从而帮助解决这一问题。这些人工代理可以在任何时间回答一般查询,增加了扩展服务的可访问性。随着自然语言处理(NLP)的进步及其在云服务中的可访问性,创建上下文化解决方案成为可能。我们写这篇论文是为了收集农业对话代理和用于其设计和部署的工具的最新研究。收集有关当前应用程序的一般知识,并可在以后难以获得农业服务时用于帮助设计本地化解决方案。最后,我们描述和分析了一个使用IBM Watson服务和消息平台Telegram App的香蕉种植特定领域的聊天机器人原型。
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