Fusing information from many different sources to be able to estimate where it is likely to find survivors.
It is often difficult to coordinate and plan the rescue work after a disaster such as an earthquake or a Tsunami. In this project, we aim to develop statistical models that can combine information from cameras mounted on UAVs, maps, cell tower information, etc. to create a probability map over an area. This map would tell the first responders and other emergency personnel where it is most likely to find survivors after a disaster. Hence, this can be used to have the lives or more people trapped in the rubble of collapsed buildings, etc. These models need to be constructed in real-time as more information is collected from the area. Hence, efficient computational methods are required and developing these are also a major aim of this project.
Image is used under Creative Commons with credits to Mark Dixon on FlickR.