This paper presents an artificial intelligence (AI) based decision support system to assist call takers sitting behind emergency numbers, such as 1-1-2 or 9-1-1. Accurate situational awareness of emergency incidents during emergency report intake is crucial for the initial response. However, the caller’s utterances in an emergency situation can be uncertain, therefore the AI model can often assist call recipients with false predictions, delaying the appropriate initial response to emergencies. To address this issue, we propose using an uncertainty-aware AI model in the decision support system. The proposed system displays a set of emergency situational candidates predicted based on the text transcribed in real-time as the voice report intake, supporting the call takers in effectively receiving the emergency calls. The type and number of emergency situational candidates are determined considering the uncertainty inferred from an uncertainty-aware AI model. We provide a detailed explanation of the proposed system and evaluate its performance using actual domestic 1-1-2 police emergency report data.
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J. Kim et. al, "Trends in Lightweight Kernel for Many core Based High-Performance Computing", Electronics and Telecommunications Trends. Vol. 32, No. 4, 2017, KOGL Type 4: Source Indication + Commercial Use Prohibition + Change Prohibition
J. Sim et.al, “the Fourth Industrial Revolution and ICT – IDX Strategy for leading the Fourth Industrial Revolution”, ETRI Insight, 2017, KOGL Type 4: Source Indication + Commercial Use Prohibition + Change Prohibition
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