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Bus Indoor Situation Monitoring System Based on Congestion Model Using Lightweight Platform

Authors:
Dong Hyun Kim
Yun Seob Kim
Jong Deok Kim

Keywords: Congestion model, Indoor situation monitoring, Lightweight platform.

Abstract:
The utilization of data is becoming increasingly prevalent across various domains including public services, security, transportation, marketing, and more, leading to a growing interest in data utilization. Especially in the case of public buses, which are heavily used by many people, the importance of congestion is increasingly recognized due to its direct correlation with safety and the potential for numerous associated problems. The bus indoor situation monitoring system aims to predict bus interior congestion and ensure passenger safety through the use of Internet of Things (IoT) and artificial intelligence technology. This paper designs and implements a bus indoor situation monitoring system based on artificial intelligence to predict congestion inside the bus, demonstrating its practicality.

Pages: 174 to 179

Copyright: Copyright (c) IARIA, 2024

Publication date: June 30, 2024

Published in: conference

ISBN: 978-1-68558-180-0

Location: Porto, Portugal

Dates: from June 30, 2024 to July 4, 2024