Enhancing Maritime Domain Awareness Through AI-Enabled Acoustic Buoys for Real-Time Detection and Tracking of Fast-Moving Vessels
Acoustic target recognition has always played a central role in marine sensing. Traditional signal processing techniques that have been used for target recognition have shown limitations in accuracy, particularly with commodity hardware. To address such limitations, we present the results of our exp...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/6/1930 |
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| author | Jeremy Karst Robert McGurrin Kimberly Gavin Joseph Luttrell William Rippy Robert Coniglione Jason McKenna Ralf Riedel |
| author_facet | Jeremy Karst Robert McGurrin Kimberly Gavin Joseph Luttrell William Rippy Robert Coniglione Jason McKenna Ralf Riedel |
| author_sort | Jeremy Karst |
| collection | DOAJ |
| description | Acoustic target recognition has always played a central role in marine sensing. Traditional signal processing techniques that have been used for target recognition have shown limitations in accuracy, particularly with commodity hardware. To address such limitations, we present the results of our experiments to assess the capabilities of AI-enabled acoustic buoys using OpenEar™, a commercial, off-the-shelf, software-defined hydrophone sensor, for detecting and tracking fast-moving vessels. We used a triangular sparse sensor network to investigate techniques necessary to estimate the detection, classification, localization, and tracking of boats transiting through the network. Emphasis was placed on evaluating the sensor’s operational detection range and feasibility of onboard AI for cloud-based data fusion. Results indicated effectiveness for enhancing maritime domain awareness and gaining insight into illegal, unreported, and unregulated activities. Additionally, this study provides a framework for scaling autonomous sensor networks to support persistent maritime surveillance. |
| format | Article |
| id | doaj-art-eceb48efe5cc40a0bacf8e822f7902b5 |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-eceb48efe5cc40a0bacf8e822f7902b52025-08-20T02:43:07ZengMDPI AGSensors1424-82202025-03-01256193010.3390/s25061930Enhancing Maritime Domain Awareness Through AI-Enabled Acoustic Buoys for Real-Time Detection and Tracking of Fast-Moving VesselsJeremy Karst0Robert McGurrin1Kimberly Gavin2Joseph Luttrell3William Rippy4Robert Coniglione5Jason McKenna6Ralf Riedel7Roger F. Wicker Center for Ocean Enterprise, The University of Southern Mississippi, Gulfport, MS 39501, USABLUEiQ, 10 Fan Pier Boulevard, Boston, MA 02210, USABLUEiQ, 10 Fan Pier Boulevard, Boston, MA 02210, USARoger F. Wicker Center for Ocean Enterprise, The University of Southern Mississippi, Gulfport, MS 39501, USARoger F. Wicker Center for Ocean Enterprise, The University of Southern Mississippi, Gulfport, MS 39501, USARoger F. Wicker Center for Ocean Enterprise, The University of Southern Mississippi, Gulfport, MS 39501, USARoger F. Wicker Center for Ocean Enterprise, The University of Southern Mississippi, Gulfport, MS 39501, USARoger F. Wicker Center for Ocean Enterprise, The University of Southern Mississippi, Gulfport, MS 39501, USAAcoustic target recognition has always played a central role in marine sensing. Traditional signal processing techniques that have been used for target recognition have shown limitations in accuracy, particularly with commodity hardware. To address such limitations, we present the results of our experiments to assess the capabilities of AI-enabled acoustic buoys using OpenEar™, a commercial, off-the-shelf, software-defined hydrophone sensor, for detecting and tracking fast-moving vessels. We used a triangular sparse sensor network to investigate techniques necessary to estimate the detection, classification, localization, and tracking of boats transiting through the network. Emphasis was placed on evaluating the sensor’s operational detection range and feasibility of onboard AI for cloud-based data fusion. Results indicated effectiveness for enhancing maritime domain awareness and gaining insight into illegal, unreported, and unregulated activities. Additionally, this study provides a framework for scaling autonomous sensor networks to support persistent maritime surveillance.https://www.mdpi.com/1424-8220/25/6/1930acoustic target recognitionmarine domain awareness (MDA)OpenEar™artificial intelligencelocalization |
| spellingShingle | Jeremy Karst Robert McGurrin Kimberly Gavin Joseph Luttrell William Rippy Robert Coniglione Jason McKenna Ralf Riedel Enhancing Maritime Domain Awareness Through AI-Enabled Acoustic Buoys for Real-Time Detection and Tracking of Fast-Moving Vessels Sensors acoustic target recognition marine domain awareness (MDA) OpenEar™ artificial intelligence localization |
| title | Enhancing Maritime Domain Awareness Through AI-Enabled Acoustic Buoys for Real-Time Detection and Tracking of Fast-Moving Vessels |
| title_full | Enhancing Maritime Domain Awareness Through AI-Enabled Acoustic Buoys for Real-Time Detection and Tracking of Fast-Moving Vessels |
| title_fullStr | Enhancing Maritime Domain Awareness Through AI-Enabled Acoustic Buoys for Real-Time Detection and Tracking of Fast-Moving Vessels |
| title_full_unstemmed | Enhancing Maritime Domain Awareness Through AI-Enabled Acoustic Buoys for Real-Time Detection and Tracking of Fast-Moving Vessels |
| title_short | Enhancing Maritime Domain Awareness Through AI-Enabled Acoustic Buoys for Real-Time Detection and Tracking of Fast-Moving Vessels |
| title_sort | enhancing maritime domain awareness through ai enabled acoustic buoys for real time detection and tracking of fast moving vessels |
| topic | acoustic target recognition marine domain awareness (MDA) OpenEar™ artificial intelligence localization |
| url | https://www.mdpi.com/1424-8220/25/6/1930 |
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