AI-enhanced crowdsourcing for disaster
management: strengthening community
resilience through social media

AI-enhanced crowdsourcing for disaster
management: strengthening community
resilience through social media

Disaster management, Community resilience, Social media analytics, Artificial intelligence, Crowdsourcing,
AI-enhanced crowdsourcing

Abstract
As disasters become more frequent and complex, the integration of artificial intelligence (AI) with crowdsourced
data from social media is emerging as a powerful approach to enhance disaster management and community
resilience. This study investigates the potential of AI-enhanced crowdsourcing to improve emergency preparedness
and response. A systematic review was conducted using both qualitative and quantitative methodologies, guided
by the PRISMA framework, to identify and evaluate relevant literature. The findings reveal that AI systems can
effectively process real-time social media data to deliver timely alerts, coordinate emergency actions, and engage
communities. Key themes explored include the effectiveness of community participation, AI’s capacity to manage
large-scale information flows, and the challenges posed by misinformation, data privacy, and infrastructural
limitations. The results suggest that when strategically implemented, AI-enhanced crowdsourcing can play a critical
role in building adaptive and sustainable disaster management frameworks. The paper concludes with practical
and policy-level recommendations for integrating these technologies into Pakistan’s disaster management systems.
Keywords Disaster management, Community resilience, Social media analytics, Artificial intelligence, Crowdsourcing,
AI-enhanced crowdsourcing

Sheikh Kamran Abid1*, Ruhizal Roosli1

, Umber Nazir2

and Nur Shazwani Kamarudin2

https://doi.org/10.1186/s12245-025-01009-9

2025

Peri Irawan

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