Developing an Emergency Communications Framework Using Unmanned Arial Vehicles
Location
Nessmith-Lane Atrium
Session Format
Poster Presentation
Research Area Topic:
Engineering and Material Sciences - Electrical
Abstract
Natural disasters are destructive to both life and property. After a disaster such as a hurricane or flood has struck there are often many people who need assistance from search and rescue workers; however, the same events that harm so many lives usually also take out critical infrastructure including cellular communication networks. If emergency cellular service could be restored to these areas quickly after a disaster, then victims could contact first responders with their cellphones. This could allow more people to be rescued by minimizing the amount of time usually spent looking for survivors in need of assistance.
Past research has shown how autonomous aerial vehicles could be utilized to restore critical communications infrastructure. While these systems are useful they are restricted by the large amount of power required to keep a UAV airborne. A modified version of this system could autonomously survey a disaster site, determine optimal node locations, and land UAVs at those locations. These UAVs should then provide emergency cellular services to users directly with an omnidirectional radio, while forming a line of sight based backbone network between themselves and an area where a tie in to functioning infrastructure is possible.
One of the most important parts of a system for emergency cellular services that does not intend to remain airborne while operating is picking where each node should land. These locations should be chosen to optimize the number of potential victims covered by the network without compromising the backbone communications of that network. The objective of this research is to develop an algorithm that takes in a depth map with specified infrastructure tie in point(s) and determine an optimal placement for a fixed number of nodes to create a cellular network in the mapped area.
In order to determine the proper set of node locations different optimization algorithms are being evaluated for performance and accuracy. The main parameter that cannot be compromised is a line of sight link between each node and two of its fellows. These links must be maintained to provide failure tolerance to the network. Additional parameters include limits on maximum transmission power for the end user radio and the backbone communications radio as well as the stability of node locations and the difficulty of successfully landing a UAV at a given point. These calculations are being performed assuming the lowest frequency band, 850 MHz, commonly supported by devices from the two largest cellular providers in the US, AT&T and Verizon in order to maximize penetration of the signals into buildings and rubble. The output of this optimization is a set of 3D coordinates marking where nodes should be placed in the network along with the orientation of their directional backbone antennas.
Creative Commons License
Digital Commons@Georgia Southern License
Presentation Type and Release Option
Event
Start Date
4-16-2016 2:45 PM
End Date
4-16-2016 4:00 PM
Recommended Citation
Holcomb, Sterling, "Developing an Emergency Communications Framework Using Unmanned Arial Vehicles" (2016). GS4 Georgia Southern Student Scholars Symposium. 94.
https://digitalcommons.georgiasouthern.edu/research_symposium/2016/2016/94
Developing an Emergency Communications Framework Using Unmanned Arial Vehicles
Nessmith-Lane Atrium
Natural disasters are destructive to both life and property. After a disaster such as a hurricane or flood has struck there are often many people who need assistance from search and rescue workers; however, the same events that harm so many lives usually also take out critical infrastructure including cellular communication networks. If emergency cellular service could be restored to these areas quickly after a disaster, then victims could contact first responders with their cellphones. This could allow more people to be rescued by minimizing the amount of time usually spent looking for survivors in need of assistance.
Past research has shown how autonomous aerial vehicles could be utilized to restore critical communications infrastructure. While these systems are useful they are restricted by the large amount of power required to keep a UAV airborne. A modified version of this system could autonomously survey a disaster site, determine optimal node locations, and land UAVs at those locations. These UAVs should then provide emergency cellular services to users directly with an omnidirectional radio, while forming a line of sight based backbone network between themselves and an area where a tie in to functioning infrastructure is possible.
One of the most important parts of a system for emergency cellular services that does not intend to remain airborne while operating is picking where each node should land. These locations should be chosen to optimize the number of potential victims covered by the network without compromising the backbone communications of that network. The objective of this research is to develop an algorithm that takes in a depth map with specified infrastructure tie in point(s) and determine an optimal placement for a fixed number of nodes to create a cellular network in the mapped area.
In order to determine the proper set of node locations different optimization algorithms are being evaluated for performance and accuracy. The main parameter that cannot be compromised is a line of sight link between each node and two of its fellows. These links must be maintained to provide failure tolerance to the network. Additional parameters include limits on maximum transmission power for the end user radio and the backbone communications radio as well as the stability of node locations and the difficulty of successfully landing a UAV at a given point. These calculations are being performed assuming the lowest frequency band, 850 MHz, commonly supported by devices from the two largest cellular providers in the US, AT&T and Verizon in order to maximize penetration of the signals into buildings and rubble. The output of this optimization is a set of 3D coordinates marking where nodes should be placed in the network along with the orientation of their directional backbone antennas.
