The Effect of COVID-19 on the Transit System in Two Regions: Japan and USA
2021 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2021
; : 51-56, 2021.
Article
in English
| Scopus | ID: covidwho-1769582
ABSTRACT
The communication revolution that happened in the last ten years has increased the use of technology in the transportation world. Intelligent Transportation Systems wish to predict how many buses are needed in a transit system. With the pandemic effect that the world has faced since early 2020, it is essential to study the impact of the pandemic on the transit system. This paper proposes the leverage of Internet of Things (IoT) devices to predict the number of bus ridership before and during the pandemic. We compare the collected data from Kobe city, Hyogo, Japan, with data gathered from a college city in Virginia, USA. Our goal is to show the effect of the pandemic on ridership through the year 2020 in two different countries. The ultimate goal is to help transit system managers predict how many buses are needed if another pandemic hits. © 2021 IEEE.
Case Studies; COVID-19; Intelligent Transportation Systems (ITS); Internet of Things (IoT); Transit Systems; Bus transportation; Buses; Forecasting; Intelligent vehicle highway systems; Internet of things; Case-studies; Intelligent transportation system; Intelligent transportation systems; Internet of thing; Virginia; Intelligent systems
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Language:
English
Journal:
2021 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2021
Year:
2021
Document Type:
Article
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