Intelligent Agent for Hurricane Emergency Identification and Text Information Extraction from Streaming Social Media Big Data

TL;DR

This paper develops an AI-powered intelligent agent that processes streaming social media data during hurricanes to identify rescue requests, extract critical information, and assist emergency response efforts.

Contribution

It introduces a prototype system that leverages real-time social media data and AI for disaster response, addressing limitations of traditional emergency call centers.

Findings

Successful real-time tweet collection during Hurricane Harvey

Effective extraction of rescue requests and geolocation data

Potential to enhance emergency response coordination

Abstract

This paper presents our research on leveraging social media Big Data and AI to support hurricane disaster emergency response. The current practice of hurricane emergency response for rescue highly relies on emergency call centres. The more recent Hurricane Harvey event reveals the limitations of the current systems. We use Hurricane Harvey and the associated Houston flooding as the motivating scenario to conduct research and develop a prototype as a proof-of-concept of using an intelligent agent as a complementary role to support emergency centres in hurricane emergency response. This intelligent agent is used to collect real-time streaming tweets during a natural disaster event, to identify tweets requesting rescue, to extract key information such as address and associated geocode, and to visualize the extracted information in an interactive map in decision supports. Our experiment shows promising outcomes and the potential application of the research in support of hurricane emergency response.