TY - GEN
T1 - Bus Crowdedness Sensing System Based on Carbon Dioxide Concentration
AU - Huang, Wenhao
AU - Tsuge, Akira
AU - Chen, Yin
AU - Okoshi, Tadashi
AU - Nakazawa, Jin
N1 - Funding Information:
Thanks for support of Kanagawa Chuo Kotsu Co., Ltd. in the actual route bus demonstration experiment. This R&D includes the research activities which is commissioned by the National Institute of Information and Communications Technology (accession number 222B02). This work was also partly supported by JSPS A3 Foresight Program, (grant No. JPJSA3F20200001).
Publisher Copyright:
© 2022 Owner/Author.
PY - 2022/11/6
Y1 - 2022/11/6
N2 - Crowdedness sensing of buses is playing an important role in the disease control of COVID-19 and bus resource scheduling. This research analyzes the relationship between carbon dioxide concentration, bus environment and the number of passengers by linear regression. Our prototype system collects the data of bus environment and carbon dioxide concentration to estimate the number of passengers in real time. By collecting the sensing data from a shuttle bus of university campus, we experimentally evaluate the feasibility and sensing performance of the crowdedness estimation model.
AB - Crowdedness sensing of buses is playing an important role in the disease control of COVID-19 and bus resource scheduling. This research analyzes the relationship between carbon dioxide concentration, bus environment and the number of passengers by linear regression. Our prototype system collects the data of bus environment and carbon dioxide concentration to estimate the number of passengers in real time. By collecting the sensing data from a shuttle bus of university campus, we experimentally evaluate the feasibility and sensing performance of the crowdedness estimation model.
KW - carbon dioxide sensor
KW - crowdedness sensing
KW - smart cities
KW - ubiquitous computing
UR - http://www.scopus.com/inward/record.url?scp=85147548272&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85147548272&partnerID=8YFLogxK
U2 - 10.1145/3560905.3568051
DO - 10.1145/3560905.3568051
M3 - Conference contribution
AN - SCOPUS:85147548272
T3 - SenSys 2022 - Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems
SP - 806
EP - 807
BT - SenSys 2022 - Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems
PB - Association for Computing Machinery, Inc
T2 - 20th ACM Conference on Embedded Networked Sensor Systems, SenSys 2022
Y2 - 6 November 2022 through 9 November 2022
ER -
