3D Multibeam Echo Sounder Data Processing Using Distributed Computing. Application To False Alarm Reduction And Unsupervised Underwater Object Recognition For Safe Navigation

The goal of this study is to take advantage of artificial intelligence (AI) algorithms and distributed computing ecosystem to enhance the 3D-multibeam echo sounder data processing functionality. We consider first the post processing case, where a complete dataset has been recorded during sea trials....

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Bibliographic Details
Published inOCEANS 2019 - Marseille pp. 1 - 7
Main Authors Matte, G., Chaillan, F., Heinzle, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2019
Subjects
Big Data
Clustering algorithms
Data processing
Data visualization
Decision making
distributed computing
Distributed databases
false alarm reduction
forward looking echo sounder
Object recognition
Real-time systems
sea trials
Sonar navigation
underwater object recognition
unsupervised learning
volumic imaging
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Summary:The goal of this study is to take advantage of artificial intelligence (AI) algorithms and distributed computing ecosystem to enhance the 3D-multibeam echo sounder data processing functionality. We consider first the post processing case, where a complete dataset has been recorded during sea trials. Hence, our suggested framework designed for massive real world data processing allows employing false alarm reduction and underwater object recognition techniques, which can be easily used as decision making for underwater autonomous vehicle safe navigation.
DOI:10.1109/OCEANSE.2019.8867293