Potential Applications for Natural Language Processing in Agriculture |
Paper ID : 1160-NICAME1402 |
Authors: |
Soleiman Hosseinpour *1, Pouya rezvani Asl2 1Faculty of Agriculture, University of Tehran, Iran 2Faculty of Agriculture, University of Tehran |
Abstract: |
Natural Language Processing (NLP) is a technology that gives the ability to software and computer systems to evaluate, understand, and act on requests and textual data. NLP has numerous applications in various fields, including agriculture. In digital agriculture, NLP techniques can be used to analyze and process large collections of agricultural documents such as social media, scientific papers, news, etc. NLP can also be used for the Semantic Analysis of requirements for controlling sensors, drones, cameras, and other technologies in Agriculture. One of the main uses of NLP in agriculture is crop monitoring, where farmers can be aware of crop growth and health by analyzing data from sensors, satellite images, and weather forecasts. NLP techniques can also be used to discover crop disease, Supply Chain Logistics, Soil Analysis, and Quality Assurance trends using farmer queries. This article emphasizes the recent development and the potential application of this important and emerging research area by discussing original research, surveys, and position papers that address issues in Agricultural Text Mining or Agri Semantics. Overall, NLP techniques have the potential to revolutionize agriculture and food science. |
Keywords: |
Machin Learning, Deep Learning, Natural Language Processing, Digital Agriculture, Chatbot |
Status : Paper Accepted (Oral Presentation) |