AI-Driven Disaster Response and Displacement Monitoring

Noora Al-Emadi; Muhammad Imran; Yin Yang; Ingmar Weber; Fabjan Lashi; Gaia Rigodanza; Ivana Hajžmanová; Ferda Ofli

doi:10.1145/3737449

AI-Driven Disaster Response and Displacement Monitoring

Noora Al-Emadi, Muhammad Imran, Yin Yang, Ingmar Weber, Fabjan Lashi, Gaia Rigodanza, Ivana Hajžmanová, Ferda Ofli

Qatar Computing Research Institute

Research output: Contribution to journal › Article › peer-review

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,¹³ control and design of renewable energy,² and monitoring deforestation.¹⁹ Machine learning algorithms analyze satellite imagery and socioeconomic data to predict poverty¹¹ and promote sustainable development.⁴ AI has also transformed disaster response and conflict monitoring, providing innovative solutions for assessing damage and urgent needs⁹ and tracking displacement.²⁰

Original language	English
Pages (from-to)	66-71
Number of pages	6
Journal	Communications of the ACM
Volume	68
Issue number	10
DOIs	https://doi.org/10.1145/3737449
Publication status	Published - 1 Oct 2025

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title = "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{\textquoteright}s most pressing challenges. For instance, in addressing climate change, AI-powered models are being used for faster and more accurate global weather forecasting,13 control and design of renewable energy,2 and monitoring deforestation.19 Machine learning algorithms analyze satellite imagery and socioeconomic data to predict poverty11 and promote sustainable development.4 AI has also transformed disaster response and conflict monitoring, providing innovative solutions for assessing damage and urgent needs9 and tracking displacement.20",

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AU - Al-Emadi, Noora

AU - Imran, Muhammad

AU - Yang, Yin

AU - Weber, Ingmar

AU - Lashi, Fabjan

AU - Rigodanza, Gaia

AU - Hajžmanová, Ivana

AU - Ofli, Ferda

PY - 2025/10/1

Y1 - 2025/10/1

N2 - 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,13 control and design of renewable energy,2 and monitoring deforestation.19 Machine learning algorithms analyze satellite imagery and socioeconomic data to predict poverty11 and promote sustainable development.4 AI has also transformed disaster response and conflict monitoring, providing innovative solutions for assessing damage and urgent needs9 and tracking displacement.20

AB - 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,13 control and design of renewable energy,2 and monitoring deforestation.19 Machine learning algorithms analyze satellite imagery and socioeconomic data to predict poverty11 and promote sustainable development.4 AI has also transformed disaster response and conflict monitoring, providing innovative solutions for assessing damage and urgent needs9 and tracking displacement.20

UR - https://www.scopus.com/pages/publications/105019702089

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JO - Communications of the ACM

JF - Communications of the ACM

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AI-Driven Disaster Response and Displacement Monitoring

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