Title:	REPORT ON ESTIMATING RICE FIELD QUALITY USING ARTIFICIAL INTELLIGENCE
Author(s):	Yahjeb Bouha Khatraty, Nedra Mellouli Nauwynck, Mamadou Tourad Diallo and Mohamedade Farouk Nanne
ISBN:	978-989-8704-32-0
Editors:	Yingcai Xiao, Ajith Abraham and Guo Chao Peng
Year:	2021
Edition:	Single
Keywords:	Machine Learning, Internet of Things, Intelligent rice paddies, Grain Yield Prediction
Type:	Reflection
First Page:	166
Last Page:	170
Language:	English
Cover:
Full Contents:	click to dowload
Paper Abstract:	The use of artificial intelligence has made life easier for farmers, as analysis of agricultural data allows farmers to make informed decisions, supported by large data sets and processed by machine learning algorithms. In this paper, we present the literature on rice quality assessment according to the different criteria and factors used to predict the quality or yield of rice. Thus, we provided a list of machine learning and deep learning models that had high accuracy in predicting rice yield and quality. In addition, due to the lack of literature of a real-time rice field monitoring system, we proposed a real-time rice field condition monitoring system that collects weather and soil condition data and sends them to the web server. The farmer can see the status of its remotely field and can automate certain tasks such as irrigation based on the collected data values.
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