Cloud-Based Architecture for Hydrophone Data Acquisition and Processing of Surface and Underwater Vehicle Detection
I tiakina i:
| I whakaputaina i: | Journal of Marine Science and Engineering vol. 13, no. 8 (2025), p. 1455-1476 |
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| Kaituhi matua: | |
| Ētahi atu kaituhi: | , , , , |
| I whakaputaina: |
MDPI AG
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| Ngā marau: | |
| Urunga tuihono: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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MARC
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| 003 | UK-CbPIL | ||
| 022 | |a 2077-1312 | ||
| 024 | 7 | |a 10.3390/jmse13081455 |2 doi | |
| 035 | |a 3244043866 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231479 |2 nlm | ||
| 100 | 1 | |a Pérez, Carrasco Francisco |u FAV Innovation and Technologies, 46006 Valencia, Spain; fperez@favit.es (F.P.C.); agarcia@favit.es (A.G.) | |
| 245 | 1 | |a Cloud-Based Architecture for Hydrophone Data Acquisition and Processing of Surface and Underwater Vehicle Detection | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This paper presents a cloud-based architecture for the acquisition, transmission, and processing of acoustic data from hydrophone arrays, designed to enable the detection and monitoring of both surface and underwater vehicles. The proposed system offers a modular and scalable cloud infrastructure that supports real-time and distributed processing of hydrophone data collected in diverse aquatic environments. Acoustic signals captured by heterogeneous hydrophones—featuring varying sensitivity and bandwidth—are streamed to the cloud, where several machine learning algorithms can be deployed to extract distinguishing acoustic signatures from vessel engines and propellers in interaction with water. The architecture leverages cloud-based services for data ingestion, processing, and storage, facilitating robust vehicle detection and localization through propagation modeling and multi-array geometric configurations. Experimental validation demonstrates the system’s effectiveness in handling high-volume acoustic data streams while maintaining low-latency processing. The proposed approach highlights the potential of cloud technologies to deliver scalable, resilient, and adaptive acoustic sensing platforms for applications in maritime traffic monitoring, harbor security, and environmental surveillance. | |
| 653 | |a Data acquisition | ||
| 653 | |a Ingestion | ||
| 653 | |a Bandwidths | ||
| 653 | |a Propellers | ||
| 653 | |a Signal processing | ||
| 653 | |a Hydrophones | ||
| 653 | |a Modularity | ||
| 653 | |a Machine learning | ||
| 653 | |a Localization | ||
| 653 | |a Fault tolerance | ||
| 653 | |a Underwater vehicles | ||
| 653 | |a Acoustic data | ||
| 653 | |a Vehicles | ||
| 653 | |a Propagation | ||
| 653 | |a Acoustics | ||
| 653 | |a Target recognition | ||
| 653 | |a Classification | ||
| 653 | |a Network latency | ||
| 653 | |a Arrays | ||
| 653 | |a Algorithms | ||
| 653 | |a Latency | ||
| 653 | |a Real time | ||
| 653 | |a Cloud computing | ||
| 653 | |a Aquatic environment | ||
| 653 | |a Harbors | ||
| 653 | |a Ports | ||
| 653 | |a Data processing | ||
| 653 | |a Data transmission | ||
| 653 | |a Monitoring | ||
| 653 | |a Distributed processing | ||
| 653 | |a Acoustic imagery | ||
| 653 | |a Modular systems | ||
| 653 | |a Sensors | ||
| 653 | |a Neural networks | ||
| 653 | |a Design | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Fernández García Anaida |u Grupo de Aplicación de Telecomunicaciones Visuales (GATV), Universidad Politécnica de Madrid, 28040 Madrid, Spain; anaida.fernandez@upm.es (A.F.G.); veronica.ruiz@upm.es (V.R.B.); alberto.belmonte@upm.es (A.B.-H.) | |
| 700 | 1 | |a García, Alberto |u FAV Innovation and Technologies, 46006 Valencia, Spain; fperez@favit.es (F.P.C.); agarcia@favit.es (A.G.) | |
| 700 | 1 | |a Ruiz, Bejerano Verónica |u Grupo de Aplicación de Telecomunicaciones Visuales (GATV), Universidad Politécnica de Madrid, 28040 Madrid, Spain; anaida.fernandez@upm.es (A.F.G.); veronica.ruiz@upm.es (V.R.B.); alberto.belmonte@upm.es (A.B.-H.) | |
| 700 | 1 | |a Gutiérrez Álvaro |u ETSI Telecomunicación, Universidad Politécnica de Madrid, 28040 Madrid, Spain | |
| 700 | 1 | |a Belmonte-Hernández, Alberto |u Grupo de Aplicación de Telecomunicaciones Visuales (GATV), Universidad Politécnica de Madrid, 28040 Madrid, Spain; anaida.fernandez@upm.es (A.F.G.); veronica.ruiz@upm.es (V.R.B.); alberto.belmonte@upm.es (A.B.-H.) | |
| 773 | 0 | |t Journal of Marine Science and Engineering |g vol. 13, no. 8 (2025), p. 1455-1476 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3244043866/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3244043866/fulltextwithgraphics/embedded/H09TXR3UUZB2ISDL?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3244043866/fulltextPDF/embedded/H09TXR3UUZB2ISDL?source=fedsrch |