We're using a connectionless protocol to account for intermittent connectivity in order to closely monitor personnel and disaster relief on the field regardless of network strength!
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
SimulationPKG
README.md
ebola.str
phys_client.c
phys_serv.c
server_script.py
technicalreport.txt

README.md

AFRL Problem: Personnel Monitoring with Intermittent Data Connection

By: Joe Baylor, David McAffee , Benjamin Natarian, Val Red, Devin Spatz

This is the development repository for LabHack 2014, USAF AFRL's first hackathon! Specifically, this github repo will include the server-client C files used to address the AFRL "Spotty Data Connection for Personnel Monitoring" problem.

High-level overview

Our solution for addressing intermittent data connection is by applying the simplicity and robustness of the User Datagram Protocol, UDP, and amplifying it with high-frequency, by-the-minute
check-ins using customized, standardized datagrams such that reliability is maximized in spite of the potential for data-loss or corruption via weak connection sources and connection interruptions. Such risk is mitigated by aspects of server-side validation and data analysis reinforced by the near-constant device datagram firing tempo from devices belonging to personnel over large distances in cases such as disaster relief operations.

Chronological File Function Order

  1. Ebola/ -- Client-side C++ Data Gathering simulator, generates data set "ebola.str" based on theoretical scenario.
  2. ebola.str -- A sample string of datasets from a theoretical disaster relief worker.
  3. phys_client.c -- A C application that takes the data set (can be modularly substituted with raw sensor data) and interprets the data into the less-than-80 byte UDP datagram before sending the datagram over Internet to a C2 server.
  4. phys_server.c -- This C daemon receives datagrams, interprets them, and then generates individual files of space-delimited files to be further processed by Python and PHP web applications.
  5. server_script.py - This Python scripts reads the space-delimited data and then formats it into an XML-like form that can be read and presented by the PHP web application for visualization.
  6. www/ -- PHP web application - These are the web files that present all our data virtually in real-time!

Physiology Datagram RFC (feel free to comment here!)

  1. Opcode - single integer determining status (check-in, medical emergency)
  2. Environment - whether data is human or environment data.
  3. Timestamp - Uses the UNIX Epoch for timing (~4 bytes)
  4. Latitude - GPS-based coordinate (Double)
  5. Longitude - GPS-based coordinate (Double)
  6. Altitude (Integer)
  7. Electrocardiogram (ECG) (Integer)
  8. Oxygen percentage (Integer)
  9. Respiratory rate (Integer)
  10. Body temperature (Float)

In total, the above standard can communicate all vital personnel data within under 80-byte UDP payloads! This is especially reliable since this does not require datagram dis/reassembly and limits the risk of data loss or corruption.

For even further reliability, engineers with a mastery of network protocols and low-level C could condense this implementation even further to a binary 32-byte payload! Thus, the above format is highly flexible, scalable, and reliable.

Licensing

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <http://www.gnu.org/licenses/>.