IoT-based Machine Learning Comparative Models of Stream Water Parameters Forecasting for Freshwater Lobster
Water quality parameters such as dissolved oxygen, pH, and mineral content are important factors for aquaculture. Predictive analytics can predict water conditions in aquaculture and significantly reduce the mortality probability of aquaculture products. This paper applied stream predictive analytic...
Saved in:
Main Authors: | Bakhit, Abdelmoneim Ahmed, Nur Syahirah, Mohd Sabli, Mohd Faizal, Jamlos, Mohd Aminudin, Jamlos, N. H., Ramli, Muhammad Aqil, Hafizzan Nordin, Alhaj, Nura Abdalrhman, Ali, Ehtesham |
---|---|
Format: | Article |
Language: | English |
Published: |
Semarak Ilmu Publishing
2024
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/41682/1/IoT-based%20Machine%20Learning%20Comparative%20Models%20of%20Stream%20Water%20Parameters%20Forec.pdf http://umpir.ump.edu.my/id/eprint/41682/ https://doi.org/10.37934/aram.117.1.137149 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Biofloc farming with IoT and machine learning predictive water quality system
by: Bakhit, Abdelmoneim Ahmed, et al.
Published: (2022) -
Wireless monitoring and arima stream analytics system for freshwater lobster farm
by: Nur Syahirah, Mohd Sabli
Published: (2021) -
Design of a low-cost IoT-based biofloc water quality monitoring system
by: Bakhit, Abdelmoneim Ahmed, et al.
Published: (2024) -
A comprehensive review of sensor-based and spectroscopy-based systems for monitoring water quality in freshwater aquaculture system
by: Ali, Ehtesham, et al.
Published: (2024) -
Sustainability of fertigation in agricultural crop production by IoT system: A review
by: Nur Syahirah, Mohd Sabli, et al.
Published: (2021)