Monitoring Critical Infrastructure Facilities During Disasters Using Large Language Models

Understand

Critical Infrastructure Facilities (CIFs), such as healthcare and transportation facilities, are vital for the functioning of a community, especially during large-scale emergencies.

• In this paper, we explore a potential application of Large Language Models (LLMs) to monitor the status of CIFs affected by natural disasters through information disseminated in social media networks.
• To this end, we analyze social media data from two disaster events in two different countries to identify reported impacts to CIFs as well as their impact severity and operational status.
• We employ state-of-the-art open-source LLMs to perform computational tasks including retrieval, classification, and inference, all in a zero-shot setting.