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| − | ==Field Computer Operating Procedure==
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| − | 1. Create 'flight' folder for the data collection run
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| − | a. Execute the python program create_flight_directory_v03.py from a command window.
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| − | usage: create_flight_directory.py [-h] [-l LOG] [-f FLIGHT]
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| − | optional arguments:
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| − | -h, --help show this help message and exit
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| − | -l LOG, --log LOG The full path to apm log file.
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| − | -f FLIGHT, --flight The full path to the directory where the flight folder is to be created.
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| − | Example Command Line Invocation MAC OS X: ./create_flight_directory_v03.py -l /Users/mlucas/Desktop/"2015-01-19 09-08-54.log" -f /Users/mlucas/Desktop/
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| − | Example Command Line Invocation Windows: create_flight_directory_v03.py -l C:\Users\mlucas\Desktop\"2015-01-19 09-08-54.log" -f C:\Users\mlucas\Desktop\
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| − | Note that since the log file has a space in it, it needs to be enclosed in quotes. Alternatively, you could rename the log files to replace the space with a hyphen '-' to avoid having to use quotes.
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| − | Note also that all folder paths have to have '/' on the end to make sure that they reference the correct folder.
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| − | Example Folder Name: uas_20150119_091005_020150119
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| − | 2. Store all data for a flight in the 'flight' folder:
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| − | a. 1 operator log file e.g. DroneSettingsLog_2015-01-19_09-05-18.txt
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| − | b. 1 autopilot log file e.g. 2015-01-19-09-08-54.log
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| − | c. 1 telemetry log file e.g. 2015-01-19-09-03-03.tlog
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| − | d. All image files e.g. *.CR2. N.B. There is no need to put these in a separate sub-folder. Just copy all images to the same level as the other log files.
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| − | 3. tar the 'flight' folder. (If on Windows, 7zip will do this.)
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| − | a. filename e.g. uas_20150119_091005_020150119.tar
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| − | 4. Compute MD5 checksum for tar file. If on Windows the Microsoft utility fciv.exe will do this.
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| − | 5. Store checksum for the tar file in text file that contains the same 'flight ID' as the tarfile with '_md5.txt' appended.
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| − | Example using fciv utility:
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| − | fciv uas_20150119_091005_020150119.tar > uas_20150119_091005_020150119_md5.txt
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| − | This will output the md5 checksum to a text file. Edit the text file to remove all text except for the line with the checksum:
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| − | 427b87f05c72a0d7aea0cb2d8582aa2b uas_20150119_091005_020150119.tar
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| − | 6. Transmit data to server 'uas_staging' folder: /homes/jpoland/images/staging/uas_staging
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| − | a. Copy the tar file and the md5.txt file to the server together.
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| − | b. Ideally via sftp if not too large. Otherwise, store a copy on external hard drive and return hard drive when all runs for the experiment have been completed.
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| − | c. N.B. Keep a backup copy of data for each run on the field laptop!
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| − | ==Server Operating Procedure==
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| − | 7. Navigate to the 'incoming' folder where new run data is staged.
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| − | 8. Compute checksum for the 'flight ' data tar file and verify that it matches the value in the checksum file.
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| − | 9. Untar the 'flight' data folder.
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| − | 10. Post-process the flight data:
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| − | a. Rename each image file to a unique file name per image
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| − | b. Generate a geo-referenced metadata file for the full set of images in the run (one row per image)
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| − | i. Include a checksum for each image in the metadata
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| − | ii. N.B. The program to create the metadata could load the database table directly without having to create an intermediate metadata file for import.
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| − | 11. Perform a sanity check on geo-referenced image file to make sure that it does not contain any spurious data
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| − | a. N.B. The software for doing this is TBD. It needs to be able to read the position of every image and generate a visual plot of the flight path.
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| − | 12. Import geo-referenced image metadata file into database 'uas_images' (new) table.
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| − | a. N.B. If database is loaded by geo-referencing program directly this step is not required.
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| − | 13. Cleanup the run folder after verifying successful completion of post-processing steps
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| − | a. Delete the geo-referenced metadata file
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| − | 14. Tar the 'flight' data file folder containing the renamed image files and original log files.
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| − | 15. Compute checksum for image folder tar file.
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| − | 16. Store a record for the run into database 'uas_run' (new) table that contains at least the flight ID, checksum and notes columns.
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| − | 17. Move the 'flight' folder tar file containing the images and log files to production directory.
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| − | 18. Backup the flight data to NAS.
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