TY - GEN
T1 - Itocon - A system for visualizing the congestion of bus stops around Ito campus in real-time
T2 - 18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020
AU - Takahashi, Ryo
AU - Hayashi, Kenta
AU - Mitsukude, Yudai
AU - Futamata, Masanori
AU - Inoue, Shunei
AU - Matsuo, Shuta
AU - Ishida, Shigemi
AU - Arakawa, Yutaka
AU - Takano, Shigeru
N1 - Funding Information:
This research is supported by The Japan Science and Technology Agency (JST) through its Center of Innovation Program (COI Program) Grant Number JPMJCE1318.
Publisher Copyright:
© 2020 ACM.
PY - 2020/11/16
Y1 - 2020/11/16
N2 - Due to the spread of COVID-19, we are desired to avoid crowded places including public transportation. Kyushu University has the largest campus in Japan, called "Ito campus", and the population there is about 20,000 in which 23% of students and 46% of staff use a bus for reaching the campus. The lectures in the first half of 2020 have been conducted online, but we plan to resume face-to-face lectures gradually. At that time, we expect the bus stops and buses to be crowded, especially during rush hour. In this paper, we introduce a system, called Itocon, to visualize the human congestion of bus stops around the campus. Itocon aggregates the sensing data from various sensors deployed around the target bus stops, and calculate and visualize the congestion degrees in real-time. Itocon is developed as a web application to avoid requesting the application install. We hope all the people who use a bus change their moving time based on the congestion information for avoiding human crowds. We explain the details and the future prospects of Itocon.
AB - Due to the spread of COVID-19, we are desired to avoid crowded places including public transportation. Kyushu University has the largest campus in Japan, called "Ito campus", and the population there is about 20,000 in which 23% of students and 46% of staff use a bus for reaching the campus. The lectures in the first half of 2020 have been conducted online, but we plan to resume face-to-face lectures gradually. At that time, we expect the bus stops and buses to be crowded, especially during rush hour. In this paper, we introduce a system, called Itocon, to visualize the human congestion of bus stops around the campus. Itocon aggregates the sensing data from various sensors deployed around the target bus stops, and calculate and visualize the congestion degrees in real-time. Itocon is developed as a web application to avoid requesting the application install. We hope all the people who use a bus change their moving time based on the congestion information for avoiding human crowds. We explain the details and the future prospects of Itocon.
UR - http://www.scopus.com/inward/record.url?scp=85097543304&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85097543304&partnerID=8YFLogxK
U2 - 10.1145/3384419.3430395
DO - 10.1145/3384419.3430395
M3 - Conference contribution
AN - SCOPUS:85097543304
T3 - SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems
SP - 697
EP - 698
BT - SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems
PB - Association for Computing Machinery, Inc
Y2 - 16 November 2020 through 19 November 2020
ER -