Unsupervised Fertigation and Machine Learning for Crop Vegetation Parameter Analysis

Unsupervised Fertigation and Machine Learning for Crop Vegetation Parameter Analysis

This study proposes an IoT-based smart irrigation management system that can optimize water-resource utilization in a smart agricultural system. The system uses unsupervised learning-based clustering to predict the irrigation needs of a field based on the ground parameters sensed by automated monito...

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Bibliographic Details
Main Authors: Mohd Izzat, Mohd Rahman, Mohd Azraai, Mohd Razman, Abdul Majeed, Anwar P. P., Muhammad Nur Aiman, Shapiee, Muhammad Amirul, Abdullah, Musa, Rabiu Muazu
Format: Article
Language:English
Published: Auricle Global Society of Education and Research 2023
Subjects:
TA Engineering (General). Civil engineering (General)
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/38907/
http://umpir.ump.edu.my/id/eprint/38907/1/Unsupervised%20Fertigation%20and%20Machine%20Learning%20for%20Crop%20Vegetation%20Parameter%20Analysis.pdf

Internet

http://umpir.ump.edu.my/id/eprint/38907/
http://umpir.ump.edu.my/id/eprint/38907/1/Unsupervised%20Fertigation%20and%20Machine%20Learning%20for%20Crop%20Vegetation%20Parameter%20Analysis.pdf

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