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We (Joe Baylor, David McAffee , Benjamin Natarian, Val Red, Devin Spatz) address the LabHack AFRL Problem: Spotty Data Connection for Personnel Monitoring by implementing a robust and lightweight (under 80 bytes) UDP datagram that personnel devices can communicate to command-and-control servers at high frequency with high reliability and on-the-spot data validation, visualization, and priority escalation. This enables near real-time tracking of personnel on the field where internet connection may be intermittent (preventing traditional connection streams such as TCP) typically relied upon for communicating data. Test sensor data sets were generated in Python and C++. A C based client application parses data sets and simulates the periodic transmission of personnel data, sending the UDP datagrams across the Internet to a command-and-control server. In addition, the command-and-control server invokes a custom C-based daemon to capture and interpret the specifically-crafted UDP datagrams, creating files for a Python application to quickly process into a format that is then passed to a PHP-based scripts over Apache hosted in the same command-and-control server. All of the above segments were designed to be modular with the only constant being the order and formatting of datagram presentation that is comparable to an established protocol such as TFTP. As such, the software is highly flexible in terms of portability, usability, and scalability. This can be utilized as a great proof-of-concept for a reliable, lightweight means of constantly updating and aggregating personnel physiology data over connections that may be intermittent in vital scenarios such as disaster relief.

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