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Sewoong Hwang
Publications - 6
Citations - 43
Sewoong Hwang is an academic researcher. The author has contributed to research in topics: Smart city & Profitability index. The author has an hindex of 3, co-authored 4 publications receiving 19 citations.
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Journal ArticleDOI
Toward a Chatbot for Financial Sustainability
Sewoong Hwang,Jonghyuk Kim +1 more
TL;DR: In this paper, the authors examined the impact of customer service and chatbot on bank revenues through customer age classification and found that new product-oriented funds or housing subscription savings are more suitable for purchase through customer service than through chatbot.
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Evaluation of AI-Assisted Telemedicine Service Using a Mobile Pet Application
TL;DR: It is proved that the severity of pet diseases and the ease of use of recent AI technologies act as a moderating effect on the perception of telemedicine services through the verification of reinforcement and additional hypotheses.
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Real-Time Pedestrian Flow Analysis Using Networked Sensors for a Smart Subway System
TL;DR: This study analyzed the transfer behavior of subway pedestrians using the fingerprinting technique and developed a model that employs an AI (Artificial Intelligence)-based methodology, the cumulative visibility of moving objects (CVMO), to present the data in such a manner that it could be used to address pedestrian flow issues in this real-world implementation of smart city technology.
Journal ArticleDOI
Toward Smart Communication Components: Recent Advances in Human and AI Speaker Interaction
TL;DR: In this paper , the authors investigated how humans and artificial intelligence speakers interact and examined the interactions based on three types of communication failures: system, semantic, and effectiveness, and found that human-machine interaction using AI speaker could reach a high level through a high degree of meaning transfer.
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Optimal Planning of Real-Time Bus Information System for User-Switching Behavior
TL;DR: This study analyzes the switching behavior of traffic users according to traffic congestion time and number of transfers based on public transportation data and shows that bus-use behavior differs according to the traffic information of users and the degree of traffic congestion.