LLM-Assisted Crisis Management: Building Advanced LLM Platforms for
  Effective Emergency Response and Public Collaboration
Hakan T. Otal M. Abdullah Canbaz
Emergencies and critical incidents often unfold rapidly, necessitating a
swift and effective response. In this research, we introduce a novel approach
to identify and classify emergency situations from social media posts and
direct emergency messages using an open source Large Language Model, LLAMA2.
The goal is to harness the power of natural language processing and machine
learning to assist public safety telecommunicators and huge crowds during
countrywide emergencies. Our research focuses on developing a language model
that can understand users describe their situation in the 911 call, enabling
LLAMA2 to analyze the content and offer relevant instructions to the
telecommunicator, while also creating workflows to notify government agencies
with the caller's information when necessary. Another benefit this language
model provides is its ability to assist people during a significant emergency
incident when the 911 system is overwhelmed, by assisting the users with simple
instructions and informing authorities with their location and emergency
information.