A Novel Framework to Strengthen Early Warning Systems

Abstract

The impact of disasters on the population and environment is an important research area. Multiple criteria need to be analyzed while making policy decisions in order to control the effect of a disaster. Researchers have used many variants of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a Multi-Criteria Decision-Making (MCDM) method for prioritizing the alternatives. Additionally, the detrimental effects of disasters have compelled stakeholders to proactively prepare by strengthening crucial key elements of an Early Warning System (EWS) so that timely alerts can be produced. In this paper, a Disaster Information Provider (DIP) framework is proposed, which employs a TOPSIS variant to bolster weak elements of a people-centric EWS. Governments may utilize delivered rankings to strengthen the weak elements of the EWS in an affected area. Extensive experimentation proves the usability of the DIP framework for strengthening EWS.