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Author
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Mafundu, Precious
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Title
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AgriBot: An intelligent Assistant for Zimbabwe Virginia Tobacco farmers using natural language processing and deep learning algorithms
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Abstract
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This research focuses on the development and implementation of an intelligent interactive virtual assistant (Chabot) specifically designed for Virginia Tobacco farmers in Zimbabwe. The assistant leverages natural language processing and deep learning algorithms to enhance decision-making processes, optimize crop yield, and improve overall efficiency in the Virginia Tobacco farming systems for small to large scale growers in A1, A2 and commercial farming systems of Zimbabwe. This assistant aims to provide timely and accurate information to farmers, enabling them to make informed decisions regarding Virginia Tobacco production, disease management and pest control. The agricultural sector plays a crucial role in the economy of Zimbabwe, with tobacco farming being one of the significant contributors. However, tobacco farming faces numerous challenges, including limited access to expert advice, changing climatic conditions and minimal management. To address these challenges, the integration of intelligent interactive assistants powered by natural language processing and deep learning algorithms has emerged as a promising solution which can help in answering and advising farmers with expert knowledge regarding the best farming practices to attain higher yields. Due to continuous miserable harvests obtained by new Virginia flue cured tobacco farmers and smallholder tobacco farmers which is being attributed to lack of information, ignorance and improper farming practices here in Zimbabwe, there is a great need for more convenient, fast, reliable and sustainable technological driven mitigating strategies for assisting these farmers with real-time consultation on how to conduct proper farming practices 24/7 as recommended. The development and implementation of a Natural Language Processing (NLP) and deep learning based Chatbot has been considered as such a solution to answer these farmers' questions about best growing practices, recommended seeds, best time to plant, different ways of applying correct fertilizers, different watering practices, best recommended ways to control pests and diseases, as well as to help farmers troubleshoot problems with their crops and to recommend relevant solutions in real time. The tobacco farmer needs to know about all this, and hence the value of a Chabot to act as an Agricultural Extension Worker (AEW) and available 24/7. However, the author will build the NLP based Chatbot with Rasa and Python that can reach out to thousands of tobacco farmers across Zimbabwe to disseminate valuable information on tobacco farming techniques and recommended agricultural practices among the tobacco farmers.
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Date
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June 2024
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Publisher
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BUSE
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Keywords
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Intelligent interactive virtual assistant (Chabot),
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Natural Language Processing (NLP),
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Virginia Tobacco farmers in Zimbabwe,
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Supervisor
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Mr. Muzurura,
Precious Mafundu