We propose a multi-stage model for monitoring the Dissolved Oxygen measured continuously (every half an hour) by underwater sensors in the 'Smart Bay Santa Teresa', located on the Ligurian Eastern coast near La Spezia. This model represents the first attempt to construct a local digital twin of the bay, and it is based on three separated models for Water Temperature, Pressure (Depth) and Conductivity (Salinity). This approach enables the reconstruction of missing Dissolved Oxygen values in case of problems and failures, and also to correct the effect of biofouling on the sensors. Our procedure aims to establish a flexible framework that can be applied across various coastal environments, by leveraging both underwater sensor data and meteorological information to generate accurate descriptions and future predictions tailored to the specific study area.

A Multi-Stage Model for Dissolved Oxygen Monitoring of Coastal Seawater / Ferri, Vito; Thomas, Sele Okeoghene; Bordone, Andrea; Raiteri, Giancarlo; Ciuffardi, Tiziana; Lombardi, Chiara; Petrioli, Chiara; Spaccini, Daniele; Gjanci, Petrika; Pennecchi, Francesca; Coisson, Marco; Durin, Gianfranco. - (2024), pp. 501-506. ( 2024 IEEE International Workshop on Metrology for the Sea, MetroSea 2024 svn ) [10.1109/metrosea62823.2024.10765778].

A Multi-Stage Model for Dissolved Oxygen Monitoring of Coastal Seawater

Petrioli, Chiara;Spaccini, Daniele;Gjanci, Petrika;
2024

Abstract

We propose a multi-stage model for monitoring the Dissolved Oxygen measured continuously (every half an hour) by underwater sensors in the 'Smart Bay Santa Teresa', located on the Ligurian Eastern coast near La Spezia. This model represents the first attempt to construct a local digital twin of the bay, and it is based on three separated models for Water Temperature, Pressure (Depth) and Conductivity (Salinity). This approach enables the reconstruction of missing Dissolved Oxygen values in case of problems and failures, and also to correct the effect of biofouling on the sensors. Our procedure aims to establish a flexible framework that can be applied across various coastal environments, by leveraging both underwater sensor data and meteorological information to generate accurate descriptions and future predictions tailored to the specific study area.
2024
2024 IEEE International Workshop on Metrology for the Sea, MetroSea 2024
Biofouling; Data Cleansing; Dissolved Oxygen; Machine Learning; Neural Networks; Remote sensing; Seawater; Time Series Forecasting
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
A Multi-Stage Model for Dissolved Oxygen Monitoring of Coastal Seawater / Ferri, Vito; Thomas, Sele Okeoghene; Bordone, Andrea; Raiteri, Giancarlo; Ciuffardi, Tiziana; Lombardi, Chiara; Petrioli, Chiara; Spaccini, Daniele; Gjanci, Petrika; Pennecchi, Francesca; Coisson, Marco; Durin, Gianfranco. - (2024), pp. 501-506. ( 2024 IEEE International Workshop on Metrology for the Sea, MetroSea 2024 svn ) [10.1109/metrosea62823.2024.10765778].
File allegati a questo prodotto
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1755853
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact