AI-Driven Disaster Response and Displacement Monitoring
Abstract
ARTIFICIAL INTELLIGENCE (AI) has demonstrated its potential across a wide range of humanitarian tasks, offering scalable and data-driven solutions to some of the world's most pressing challenges. For instance, in addressing climate change, AI-powered models are being used for faster and more accurate global weather forecasting, control and design of renewable energy, and monitoring deforestation. Machine learning algorithms analyze satellite imagery and socioeconomic data to predict poverty and promote sustainable development. AI has also transformed disaster response and conflict monitoring, providing innovative solutions for assessing damage and urgent needs and tracking displacement.
Community
AI-Driven Disaster Response and Displacement Monitoring explores how artificial intelligence can support humanitarian response when conventional information sources are limited or disrupted. The article presents two case studies from the Arab world: the first uses large-scale social media data and AI models to extract actionable information following the 2023 Türkiye–Syria earthquakes, including reports of missing people, shelter needs, requests for help, and infrastructure damage; the second investigates satellite-based vehicle detection as a proxy for monitoring internal displacement during the Syrian civil war. Together, the studies demonstrate how AI can combine digital and remote-sensing data to improve situational awareness and complement traditional humanitarian information sources.
Models citing this paper 1
Datasets citing this paper 2
Spaces citing this paper 0
No Space linking this paper