Speeding up children reunification in disaster scenarios via serverless computing

Abstract

Children constitute a vulnerable population and special considerations are necessary in order to provide proper care for them during disasters. After disasters such as Hurricane Katrina, the rapid identification and protection of separated children and their reunification with legal guardians is necessary to minimize secondary injuries (i.e., physical and sexual abuse, neglect and abduction). At Camp Gruber, an Oklahoma shelter for Louisianan's displaced by Hurricane Katrina, 70% of the children were with their legal guardian after 2 weeks while the last child was reunified after 6 months. In this project, we are using serverless computing to scale and minimize database querie response time as well as to speed up machine learning tasks for rapid reunifying time, in support of a federated set of first-responders. In particular, we are using a Flask-based web system that leverages Apache OpenWhisk to run both (face and text) profile recognition software at the back-end.