Smart-Puffin Project Smart Positioning Underwater System for Environmental Field Using Artificial Intelligence

The marine environment plays a crucial role in the Earth's life cycle, but human activities threaten the marine ecosystems' natural balance. The European Union has always been committed to safeguarding marine life by the European Environment Agency. This latter promotes the establishment of Marine Protected Areas (MPAs), which are special zones of particular importance for biodiversity. These areas require constant monitoring to prevent poaching and track changes in biodiversity. According to these purposes, the project titled Smart-PUFFIN (Smart Positioning Underwater system For environmental Field using artificial Intelligence) aims to provide a low-cost solution for estimating the geographical position of underwater sound sources. The research project is centered on creating and developing an underwater positioning system to enhance monitoring efforts by an MPA or the Maritime Authority, such as the Italian Coast Guard. The system is designed to employ small buoys with two types of sensors: a GNSS (Global Navigation Satellite System) receiver for estimating the precise position of the buoy and maintaining an accurate time scale, and an omnidirectional hydrophone for listening to and recording underwater sounds. Analyzing the acquired audio signals will enable the identification of identical source sounds captured by various buoys and the subsequent computation of the source's position using the Time Differences Of Arrival (TDoA) approach. Machine Learning and Deep Learning techniques applied to the acoustic signals will be used to classify underwater sounds and correlate identical sounds from different recordings. The system should be capable of operating with cooperative targets, such as ROVs (Remotely Operated Vehicles), and non-cooperative ones, such as the hammering done by poachers of date mussels. Furthermore, it can also be employed to trace the routes taken by marine mammals in a particular area of interest.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/metrosea62823.2024.10765719
Citations
1
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.20
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Smart-Puffin Project Smart Positioning Underwater System for Environmental Field Using Artificial Intelligence

Benedetto Simone, Silvio Del Pizzo, Fabio Narducci, Salvatore Troisi et al.
1 citations
Water Quality Monitoring Technologies
0.20
article

Smart-Puffin Project Smart Positioning Underwater System for Environmental Field Using Artificial Intelligence

Benedetto Simone, Silvio Del Pizzo, Fabio Narducci, Salvatore Troisi, Ciro Gioia, Antonio Angrisano
article en
1 citations

Abstract

The marine environment plays a crucial role in the Earth's life cycle, but human activities threaten the marine ecosystems' natural balance. The European Union has always been committed to safeguarding marine life by the European Environment Agency. This latter promotes the establishment of Marine Protected Areas (MPAs), which are special zones of particular importance for biodiversity. These areas require constant monitoring to prevent poaching and track changes in biodiversity. According to these purposes, the project titled Smart-PUFFIN (Smart Positioning Underwater system For environmental Field using artificial Intelligence) aims to provide a low-cost solution for estimating the geographical position of underwater sound sources. The research project is centered on creating and developing an underwater positioning system to enhance monitoring efforts by an MPA or the Maritime Authority, such as the Italian Coast Guard. The system is designed to employ small buoys with two types of sensors: a GNSS (Global Navigation Satellite System) receiver for estimating the precise position of the buoy and maintaining an accurate time scale, and an omnidirectional hydrophone for listening to and recording underwater sounds. Analyzing the acquired audio signals will enable the identification of identical source sounds captured by various buoys and the subsequent computation of the source's position using the Time Differences Of Arrival (TDoA) approach. Machine Learning and Deep Learning techniques applied to the acoustic signals will be used to classify underwater sounds and correlate identical sounds from different recordings. The system should be capable of operating with cooperative targets, such as ROVs (Remotely Operated Vehicles), and non-cooperative ones, such as the hammering done by poachers of date mussels. Furthermore, it can also be employed to trace the routes taken by marine mammals in a particular area of interest.

University of Messina (IT), University of Salerno (IT), Parthenope University of Naples (IT)
Life below water
Openalex Percentile: Top 44%
Water Quality Monitoring Technologies
0.20
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