@article{MC6D5A219,
title = "Personal Mobility Enforcement : A MAP-API and Mixed Reality Approach with Drones for Effective Traffic Monitoring",
journal = "The Journal of Korean Institute of Communications and Information Sciences",
year = "2024",
issn = "1226-4717",
doi = "10.7840/kics.2024.49.6.893",
author = "Jun-Hyuk Woo, Ji-Hun Kim, Jae-Ryun Lee, Soo-Young Shin",
keywords = "MR(Mixed Reality), AI, Deep Learning, Traffic accident, Personal Mobility",
abstract = "Recently, the number of personal mobility users has increased worldwide. It increases the accidents due to violations of personal mobility regulations. Personal mobility requires on-the-spot crackdowns, as license plates are absent on these devices. However, the number of police officers conducting on-the-spot crackdowns is lacking due to the wide movement range of these personal mobility devices. In this paper, utilizing Map-API and Mixed Reality(MR) wearable devices to create a traffic monitoring system is proposed to solve this traffic enforcement personnel shortage. By using a proposed system with cameras, on-the-spot crackdowns on personal mobility traffic regulations can be conducted effectively. Also, unmanned devices or drones can navigate along roads, sharing the workload of traffic polices using Map-API. Utilizing the suggested system equipped with cameras can consolidate personal mobility traffic regulations on the spot. Furthermore, users, even those lacking specialized knowledge, can easily set routes using MR wearable devices and can receive live feedback from cameras and access real-time GPS information from the drones."
}