1. Ongoing thesis. Analyzing sonar data. Student: Pyojeong Kim
Advisors: Arijit Das, Sean Kragelund, Glenn Cook.

2. UUV & Mine Warfare (mission):
Image Credit:
@arijit_da

3. Sonar Data File
Each mission generates about GIG to a Terabyte of data.
Depends on the duration.
Over decades, Terabytes of files have been generated.
Files need to be catalogued (using automated techniques).
@arijit_da

4. Sonar Data File Each binary file has 2 parts. Metadata
file name, timestamp, latitude, longitude, depth and more.
Image
Extraction and processing (future thesis topic)
@arijit_da

5. Sonar Image Processing.
Image Credit:
@arijit_da

6. Cataloging: Classic Hadoop problem.
100s of thousands of files.
Same processing on each file.
Map Phase is enough to collect metadata.
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7. MapReduce.
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8. Non Hadoop processing. File format provided by the sonar vendor.
Use Java typecasting to map the raw bytes to the fields.
For large number of files:
Time consuming on single laptop, desktop, server.
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9. Oracle DB Table.
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10. Oracle Table Data.
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11. HIVE Table.
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12. HIVE Table Data.
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13. Sqoop: HDFS HIVE back to Oracle DB
Image Credit:
@arijit_da

14. Oracle DB &APEX.
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15. Hadoop in a box. ImageCredit: https://www.casesbypelican.com/
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16. AI to predict the Depth. Multilayer perceptron (MLP) regression.
Other AI Techniques.
@arijit_da