Bodenmann, Adrian 
ORCID: https://orcid.org/0000-0002-3195-0602; Liang, Cailei ORCID: https://orcid.org/0000-0002-8691-836X; Massot-Campos, Miquel; Simmons, Samuel ORCID: https://orcid.org/0009-0004-6761-9454; Phillips, Alexander B. ORCID: https://orcid.org/0000-0003-3234-8506; Consensi, Alberto ORCID: https://orcid.org/0009-0008-2254-2827; Kingsland, Matthew; Sherif, Rashiid; Brown, Stanley; Riese, Adam; Thornton, Blair ORCID: https://orcid.org/0000-0003-4492-622X.
2026
Remote Awareness of Seafloor Images Collected by AUVs Over Low-Bandwidth Communication Links.
IEEE Journal of Oceanic Engineering.
1-12.
10.1109/JOE.2026.3708604
This article introduces a method for real-time processing and transmission of autonomous underwater vehicle (AUV) imagery over low-bandwidth communication links. It leverages artificial intelligence techniques to identify a set of images that best represent an entire data set, or automatically finds the most similar images to a given query image for transmission to operators. Combined with metadata of a larger set of images, compressed versions of the selected images can be transmitted over satellite communication links or underwater modems and provide operators on shore with information about the type of imagery the AUV is collecting while it is still deployed. Data from three deployments off the coast of the U.K. and in Gran Canaria using different AUVs and imaging systems demonstrate the method in the field. It achieved an almost 400 000-fold reduction in data volume compared to the raw data size, enabling transmission of data summaries of a 2-h 47-min-long mapping mission in just over 34 min over low-bandwidth satellite communication.
NOC Research Groups 2025 > Marine Autonomous Robotic Systems
NOC Mission Networks > Sustainable Marine Economy
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