Multi-Layer Perceptron Neural Network and Internet of Things for Improving the Realtime Aquatic Ecosystem Quality Monitoring and Analysis
Dublin Core
Title
Multi-Layer Perceptron Neural Network and Internet of Things for Improving the Realtime Aquatic Ecosystem Quality Monitoring and Analysis
Subject
Aquatic ecosystem
Internet of Things
MLP
SMOTE
Description
This research proposes improving the aquarium environment for ornamental fish farming for small enterprises raising ornamental fish for sale during the COVID-19 Pandemic with an automatic aquarium system capable of forecasting the optimum environment for fish using Multi-Layer Perceptron Neural Network. Since the amount of the collected data was limited, it was also employed to adjust the imbalanced dataset by applying the Synthetic Minority OverSampling Technique to increase forecasting accuracy. Subsequently, the developed system is based on Internet of Things devices in conjunction with sensors for measuring the indicators that affect the aquarium environment, including temperature, turbidity, total dissolved solids, the potential of hydrogen ions, dissolved oxygen, and nitrate ion. Further, the mobile application was developed and collaborated with sensors and devices to facilitate entrepreneurs monitoring and controlling this automatic system. The results showed that the accuracy of the developed water environment forecasting model was 97.31% and gave the highest level of automation efficiency. Therefore, the developed automated aquarium system could be applied to reduce fish mortality and maintain environmental conditions to grow adequately over the fish life span.
Creator
Nuanmeesri, Sumitra
Poomhiran, Lap
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 06 (2022); pp. 21-40
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2022-03-22
Rights
Copyright (c) 2022 Sumitra Nuanmeesri, Lap Poomhiran
https://creativecommons.org/licenses/by/4.0
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Sumitra Nuanmeesri and Lap Poomhiran, Multi-Layer Perceptron Neural Network and Internet of Things for Improving the Realtime Aquatic Ecosystem Quality Monitoring and Analysis, International Association of Online Engineering (IAOE), Vienna, Austria, 2022, accessed November 6, 2024, https://igi.indrastra.com/items/show/2207