Automated open circuit scuba diver detection with low cost passive sonar and machine learning
Name
1117714658-MIT.pdf
Size
26.57 MB
Format
Adobe PDF
Checksum (MD5)
9b8683f169394d400f3daa8d6be92554
Author(s)
Cole, Andrew M.,Lieutenant Commander.
Advisor(s)
Carl L. Kaiser and Andone C. Lavery.
Date Issued
2019
Publisher
Massachusetts Institute of Technology
Abstract
This thesis evaluates automated open-circuit scuba diver detection using low-cost passive sonar and machine learning. Previous automated passive sonar scuba diver detection systems required matching the frequency of diver breathing transients to that of an assumed diver breathing frequency. Earlier work required prior knowledge of both the number of divers and their breathing rate. Here an image processing approach is used for automated diver detection by implementing a deep convolutional neural network. Image processing was chosen because it is a proven method for sonar classification by trained human operators. The system described here is able to detect a scuba diver from a single acoustic emission from the diver. Twenty dives were conducted in support of this work at the WHOI pier from October 2018 to February 2019. The system, when compared to a trained human operator, correctly classified approximately 93% of the data. When sequential processing techniques were applied, system accuracy rose to 97%. This demonstrated that a combination of low-cost, passive sonar and a properly tuned convolutional neural network can detect divers in a noisy environment to a range of at least 12.49 m (50 feet).
Description
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: S.M., Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 129-132).
Subjects
Joint Program in Applied Ocean Science and Engineering.
Mechanical Engineering.
Woods Hole Oceanographic Institution.
MIT Department
Joint Program in Applied Ocean Science and Engineering
Massachusetts Institute of Technology. Department of Mechanical Engineering
Woods Hole Oceanographic Institution
Terms of Use
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Persistent DSpace Link
