AI-based Approach in Early Warning Systems: Focus on Emergency Communication Ecosystem and Citizen Participation in Nordic Countries

TL;DR

This paper explores how AI technologies enhance early warning systems in Nordic countries, emphasizing emergency communication and citizen participation to improve disaster preparedness and response.

Contribution

It provides a comprehensive review of AI-enabled tools within EWSs, focusing on Nordic case studies and highlighting the importance of communication and citizen engagement.

Findings

AI improves risk modeling and mitigation in EWSs.

Enhanced emergency communication increases citizen participation.

Case studies demonstrate successful AI integration in Nordic disaster management.

Abstract

Climate change and natural disasters are recognized as worldwide challenges requiring complex and efficient ecosystems to deal with social, economic, and environmental effects. This chapter advocates a holistic approach, distinguishing preparedness, emergency responses, and postcrisis phases. The role of the Early Warning System (EWS), Risk modeling and mitigation measures are particularly emphasized. The chapter reviews the various Artificial Intelligence (AI)-enabler technologies that can be leveraged at each phase, focusing on the INFORM risk framework and EWSs. Emergency communication and psychological risk perception have been emphasized in emergency response times. Finally, a set of case studies from Nordic countries has been highlighted.