Intelligent Agent for Hurricane Emergency Identification and Text Information Extraction from Streaming Social Media Big Data
This research addresses the limitations of current emergency call centers during hurricanes by providing a complementary AI-based tool for disaster response, though it is incremental as it builds on existing social media and AI methods.
The paper tackles the problem of hurricane emergency response by developing an intelligent agent that collects real-time tweets, identifies rescue requests, extracts key information like addresses and geocodes, and visualizes data on an interactive map, showing promising outcomes for supporting emergency centers.
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.