| Title | A Multi-Stage Model for Dissolved Oxygen Monitoring of Coastal Seawater |
|---|---|
| Publication Type | Presentazione a Congresso |
| Year of Publication | 2024 |
| Authors | Ferri, Vito, Thomas Sele Okeoghene, Bordone A., Raiteri G., Ciuffardi Tiziana, Lombardi Chiara, Petrioli Chiara, Spaccini Daniele, Gjanci Petrika, Pennecchi Francesca, Coisson Marco, and Durin Gianfranco |
| Conference Name | 2024 IEEE International Workshop on Metrology for the Sea, MetroSea 2024 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Keywords | Coastal seawater, Coastal zones, Data cleansing, Direct air capture, Dissolved oxygen sensors, Lanthanum alloys, machine learning, Machine-learning, Multi stage modeling, Neural networks, Neural-networks, Oxygen monitoring, Remote-sensing, Seawater, Time series forecasting, Underwater sensors, Water temperatures |
| 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 IEEE. |
| URL | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214401008&doi=10.1109%2fMetroSea62823.2024.10765778&partnerID=40&md5=822f2e3057a1d93f247c81b944839f47 |
| DOI | 10.1109/MetroSea62823.2024.10765778 |
| Citation Key | Ferri2024501 |
