Title: Intelligent agent for hurricane emergency identification and text information extraction from streaming social media big data

Authors: Jingwei Huang; Wael Khallouli; Ghaith Rabadi; Mamadou Seck

Addresses: Department of Engineering Management and Systems Engineering, Old Dominion University, 2101 Engineering Systems Building, Norfolk, VA 23529, USA ' Department of Engineering Management and Systems Engineering, Old Dominion University, 2101 Engineering Systems Building, Norfolk, VA 23529, USA ' Department of Engineering Management and Systems Engineering, Old Dominion University, 2101 Engineering Systems Building, Norfolk, VA 23529, USA ' Department of Engineering Management and Systems Engineering, Old Dominion University, 2101 Engineering Systems Building, Norfolk, VA 23529, USA

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, to identify tweets requesting rescue, to extract key information such as address and associated geocode, and to visualise 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.

Keywords: big data; social media; Twitter; tweets; information extraction; emergency response; natural disaster; hurricane; Hurricane Harvey; flooding; intelligent agent; AI.

DOI: 10.1504/IJCIS.2023.130455

International Journal of Critical Infrastructures, 2023 Vol.19 No.2, pp.124 - 139

Received: 22 Mar 2021
Accepted: 19 May 2021
Published online: 21 Apr 2023 *

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