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Neuro-Fuzzy-Based Smart Irrigation System and Multimodal Image Analysis in Static-Clustered Wireless Sensor Network for Marigold Crops
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Author(s): Karthick Raghunath K. M. (Malla Reddy Institute of Engineering and Technology, India)and Anantha Raman G. R. (Malla Reddy Institute of Engineering and Technology, India)
Copyright: 2020
Pages: 19
Source title:
Deep Neural Networks for Multimodal Imaging and Biomedical Applications
Source Author(s)/Editor(s): Annamalai Suresh (Department of Computer Science and Engineering, Nehru Institute of Engineering and Technology, Coimbatore, India), R. Udendhran (Department of Computer Science and Engineering, Bharathidasan University, India)and S. Vimal (Department of Information Technology, National Engineering College (Autonomous), Kovilpatti, India)
DOI: 10.4018/978-1-7998-3591-2.ch015
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Abstract
As a decorative flower, marigolds have become one of the most attractive flowers, especially on the social and religious arena. Thus, this chapter reveals the potential positive resultants in the production of marigold through neuro-fuzzy-based smart irrigation technique in the static-clustered wireless sensor network. The entire system is sectionalized into clustering phase and operational phase. The clustering phase comprises three modules whereas the operational phase also includes three primary modules. The neuro-fuzzy term refers to a system that characterizes the structure of a fuzzy controller where the fuzzy sets and rules are adjusted using neural networks iteratively tuning techniques with input and output system data. The neuro-fuzzy system includes two distinct way of behavior. The vital concern of the system is to prevent unnecessary or unwarranted irrigation. Finally, on the utilization of multimodal image analysis and neuro-fuzzy methods, it is observed that the system reduces the overall utilization of water (~32-34%).
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