IoT-based prediction model for aquaponic fish pond water quality using multiscale feature fusion with convolutional autoencoder and GRU networks

IoT-based prediction model for aquaponic fish pond water quality using multiscale feature fusion with convolutional autoencoder and GRU networks

Abstract The Internet of Things (IoT)-based smart solutions have been developed to predict water quality and they are becoming an increasingly important means of providing efficient solutions through communication technologies. IoT systems are used for enabling connection between various devices bas...

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Bibliographic Details
Main Authors: Suma Christal Mary Sundararajan, Yamini Bhavani Shankar, Sinthia Panneer Selvam, Nalini Manogaran, Koteeswaran Seerangan, Deepa Natesan, Shitharth Selvarajan
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Water quality prediction
Internet of things
Aquaponic fish ponds
Revamped fitness-based mother optimization algorithm
Multi-scale feature fusion-based convolutional autoencoder with gated recurrent unit
Online Access:https://doi.org/10.1038/s41598-024-84943-7
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https://doi.org/10.1038/s41598-024-84943-7

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