Cloud-Based Architecture for Hydrophone Data Acquisition and Processing of Surface and Underwater Vehicle Detection

I tiakina i:
Ngā taipitopito rārangi puna kōrero
I whakaputaina i:Journal of Marine Science and Engineering vol. 13, no. 8 (2025), p. 1455-1476
Kaituhi matua: Pérez, Carrasco Francisco
Ētahi atu kaituhi: Fernández García Anaida, García, Alberto, Ruiz, Bejerano Verónica, Gutiérrez Álvaro, Belmonte-Hernández, Alberto
I whakaputaina:
MDPI AG
Ngā marau:
Urunga tuihono:Citation/Abstract
Full Text + Graphics
Full Text - PDF
Ngā Tūtohu: Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

MARC

LEADER 00000nab a2200000uu 4500
001 3244043866
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