ReviewInternational journal of emergency medicine2025
AI-enhanced crowdsourcing for disaster management: strengthening community resilience through social media.
Review in International journal of emergency medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.