An IoT based smart water quality assessment framework for aqua-ponds management using Dilated Spatial-temporal Convolution Neural Network (DSTCNN)

Assuring the quality of water is crucial for the growth and survival of fish in aquaculture ponds. Traditional methods of water quality monitoring can be inefficient which makes real-time monitoring and decision is a challenging one. Some deep learning techniques have shown apparent in improving wat...

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Veröffentlicht in:	Aquacultural engineering 2024-02, Vol.104, p.102373, Article 102373
Hauptverfasser:	Arepalli, Peda Gopi, Jairam Naik, K.
Format:	Artikel
Sprache:	eng
Schlagworte:	animal growth aquaculture data collection fish hybrids mortality temporal variation water quality
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