Farmer`s WhatsApp Chatbot using Natural Language processing
- Author
- Mushayavanhu, Bothwell
- Title
- Farmer`s WhatsApp Chatbot using Natural Language processing
- Abstract
- There is a great need for a quick response to farmers to assist them in any query they ask about farming practices. This is what has brought about this intelligent chatbot farmers system for farmers to get information about farming practice. This dissertation explores the design and implementation of a maize farmers' WhatsApp chatbot. The chatbot is designed to provide farmers with real-time information on maize farming best practices, market prices, weather updates, and pest and disease management. The chatbot utilizes natural language processing (NLP) and machine learning algorithms to understand and respond to farmers' queries in an efficient and user-friendly manner. The study applies a mixed-methods research approach, including qualitative research methods such as interviews and focus groups to gather data on farmers' information needs and preferences. The quantitative data is collected through surveys to evaluate the chatbot's effectiveness in providing relevant and timely information to farmers. The study concludes that the maize farmers' WhatsApp chatbot is an effective tool for providing real-time information to farmers, improving their knowledge and decision-making ability, and contributing to increased productivity and profitability. The study recommends further research on the scalability and sustainability of the chatbot, as well as its potential integration with other digital agricultural tools.
- Date
- 2023
- Publisher
- BUSE
- Keywords
- Farmer
- WhatsApp Chatbot using
- Natural Language processing
- Supervisor
- Mr. Muzurura
- Item sets
- Department of Computer Science
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