Abstract
In the aftermath of a natural disaster reconnaissance is typically conducted by teams of engineers tasked with tagging buildings according to their damage state. Tagging (red, yellow, or green) conveys information about the condition of the building (unsafe, needs further evaluation, or safe, respectively). While thorough, the process can take several days to weeks to be completed. Automated assessment is an attractive alternative to manual inspection but requires deploying a dense network of sensors at the granularity of each structure. Such a network was deemed to be impractical with respect to cost or deployment time. However, with the advent of the Internet of things (IoT) era, a massive network of citizen-owned smart devices such as tablets and smart-phones that contain vibration sensors (e.g. accelerometers) is already deployed. The objective of this work is to develop a framework that can crowd-source relatively low-quality readings from distributed smart citizen owned devices and distill that information into actionable information. This information can be provided to public safety personnel within minutes of an event, in the form of a disaster map, with buildings tagged by their most likely damage state. This paper reports on the development of an application running on a mobile phone to collect readings, and coupled to a cloud based server, used to generate the necessary tags.