AI-based Approach in Early Warning Systems: Focus on Emergency Communication Ecosystem and Citizen Participation in Nordic Countries
Shaik, Fuzel, Demil, Getnet, Oussalah, Mourad
–arXiv.org Artificial Intelligence
Climate change is a complex and multifaceted global phenomenon, characterized by long-term alterations in temperature, precipitation patterns, sea-level rise, and the increased frequency and intensity of extreme weather events. These changes are driven by anthropogenic factors, such 1 as greenhouse gas emissions, deforestation, and industrial activities, which significantly alter the Earth's natural climate systems and render the occurrence of natural disasters inevitable. Climate-related catastrophes, such as hurricanes, floods, droughts, wildfires, heatwaves, and rising sea levels, have become increasingly frequent and severe in recent years, affecting billions of people globally, and this trend is expected to continue in the future. Indeed, the Emergency Events Database (EM-DAT) estimates that between 3.3 to 3.6 billion people are exposed to extreme risk as a result of climate-related disasters (Keim, 2021). Natural disasters alone impact approximately 200 million people annually, as reported by the United Nations (UN) (Dwivedi et al., 2022). Despite major investments in advanced early warning systems (EWSs) to lessen the effects of these natural catastrophes, there still needs to be more public awareness, effective interaction with various communities, and accurate prediction to minimize societal, economic, and environmental damage.
arXiv.org Artificial Intelligence
Jun-25-2025
- Country:
- North America > United States (1.00)
- Europe > Finland (0.68)
- Genre:
- Overview (1.00)
- Industry:
- Law (1.00)
- Energy > Renewable (0.94)
- Government > Regional Government (0.93)
- Commercial Services & Supplies > Security & Alarm Services (0.86)
- Information Technology > Security & Privacy (0.70)
- Health & Medicine
- Epidemiology (0.93)
- Consumer Health (0.93)
- Therapeutic Area
- Infections and Infectious Diseases (1.00)
- Immunology (0.93)
- Technology:
- Information Technology
- Information Management (1.00)
- Architecture > Real Time Systems (0.96)
- Communications > Networks (0.93)
- Data Science
- Data Quality (1.00)
- Data Mining (1.00)
- Artificial Intelligence
- Representation & Reasoning (1.00)
- Natural Language (1.00)
- Machine Learning > Neural Networks
- Deep Learning (0.94)
- Information Technology