Machine Learning based Criticality Estimation Algorithm for Search & Rescue Operations in Collapsed Infrastructures

Abstract

Disasters cause disruptions to human life, damage public properties, and hinder the economic growth of the country. Building collapse is one of the most common disasters and causes severe loss to humans. Advanced innovative technologies such as the Internet of Things (IoT), image detection and machine learning algorithms are employed to minimize post-disaster risk factors and support rescue management. In this paper, we summarise the state of the art in rescue management and the role of advanced technologies in rescue assistance. We also propose a machine learning algorithm for first responders to safely evacuate people trapped under debris from collapsed buildings. This paper summarises the identified machine learning algorithms for this application and compares their performances with the data that we generated from the simulation setup at our laboratory.