DOIONLINE 
DOIONLINE Publish In |
International Journal of Industrial Electronics and Electrical Engineering (IJIEEE)-IJIEEE |
 Journal Home Volume Issue |
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Issue |
Volume-5,Issue-8 ( Aug, 2017 ) | |||||||||
Paper Title |
A Self-Optimizing System For Measuring and Predicting Soil Moisture Content and Leaf Wetness Level in Crop Fields | |||||||||
Author Name |
Thomas Truong, Pham Son, Anh Dinh | |||||||||
Affilition |
Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, Canada | |||||||||
Pages |
55-59 | |||||||||
Abstract |
Global crop irrigation consumes a substantial amount of the world’s freshwater withdrawals. Optimizing water usage efficiency in agricultural practices becomes a priority in ensuring global water and food security. This paper presents the design of a system which will assist crop field managers in determining the optimal irrigation schedule for their crops by providing real-time information on the soil moisture content and leaf wetness levels of their crop fields. Additionally, the system predicts the next day soil moisture content and leaf wetness levels using a self-optimizing support vector machine regression algorithm. Ultimately, the results of this system will assist crop field managers in optimizing the water usage efficiency of their crops. Keywords- Machine Learning; Weather Prediction; Precision Agriculture;Local Weather Station; Internet of Things | |||||||||
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