This poster presents an app that can help disaster affected communities find efficient and safe evacuation routes to reduce the loss of human and resources, both during and after a disaster has hit. This proposed app will navigate people seeking evacuation through suitable routes based on geographical condition, structural vulnerability, disaster severity, traffic density, human mobility, etc. The choice of most effective and safe evacuation paths primarily relies on stochastic probability of human movement and requires frequently updated data. In order to achieve this, the app uses real time GPS data by simulating the movement pattern of its users connected to network as well as their previous movement patterns when they are found offline. This simulation process will find out the less congested and safer routes for faster traversal. Users can use these path suggestions to safely drive themselves out of the disaster stricken area. In case of a user being offline, this app will use data stored on the device to suggest evacuation routes based on human mobility pattern. The implementation of this idea will help the app users evacuate safely and quickly, thus minimizing human casualty due to disaster fatality.
Hridi, Anurata Prabha; Das, Dipto; Anjum, Md Monowar; and Das, Tanmay, "Faster Evacuation after Disaster: Finding Alternative Routes using Probable Human Behavior" (2019). Graduate Research and Discovery Symposium (GRADS). 228.