TY - GEN
T1 - Evaluating the spatio-temporal coverage of automotive sensing for smart cities
AU - Chen, Yin
AU - Yonezawa, Takuro
AU - Nakazawa, Jin
AU - Tokuda, Hideyuki
N1 - Publisher Copyright:
© 2017 IPSJ.
PY - 2018/4/2
Y1 - 2018/4/2
N2 - Automotive sensing is a novel and appealing sensing technology in which sensors are installed into vehicles to utilize vehicles' mobility to conduct urban sensing in smart cities. The coverage performance is a major metric to characterizing the quality-of-service of sensing systems. Despite of the coverage metrics studied in static sensor networks that consist of only spatial dimension, the lack of a proper metric to characterizing the spatio-temporal coverage of automotive sensing systems is stunting the research, development and commercialization of such mobile sensing systems. To address this issue, we propose, for the first time to the best of our knowledge, a spatio-temporal coverage metric for automotive sensing. The proposed metric characterizes the coverage in both spatial and temporal dimensions in order to provide a guideline for smart cities application developers to evaluate the quality-of-service that can be expected from an automotive sensing system. Evaluation based on an automotive sensing system implemented in Fujisawa City, Japan is conducted to demonstrate the usage of this metric in a realistic scenario.
AB - Automotive sensing is a novel and appealing sensing technology in which sensors are installed into vehicles to utilize vehicles' mobility to conduct urban sensing in smart cities. The coverage performance is a major metric to characterizing the quality-of-service of sensing systems. Despite of the coverage metrics studied in static sensor networks that consist of only spatial dimension, the lack of a proper metric to characterizing the spatio-temporal coverage of automotive sensing systems is stunting the research, development and commercialization of such mobile sensing systems. To address this issue, we propose, for the first time to the best of our knowledge, a spatio-temporal coverage metric for automotive sensing. The proposed metric characterizes the coverage in both spatial and temporal dimensions in order to provide a guideline for smart cities application developers to evaluate the quality-of-service that can be expected from an automotive sensing system. Evaluation based on an automotive sensing system implemented in Fujisawa City, Japan is conducted to demonstrate the usage of this metric in a realistic scenario.
KW - Spatio-temporal
KW - automotive
KW - coverage
KW - smart cities
KW - urban sensing
UR - http://www.scopus.com/inward/record.url?scp=85049590591&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85049590591&partnerID=8YFLogxK
U2 - 10.23919/ICMU.2017.8330071
DO - 10.23919/ICMU.2017.8330071
M3 - Conference contribution
AN - SCOPUS:85049590591
T3 - 2017 10th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2017
SP - 1
EP - 5
BT - 2017 10th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2017
Y2 - 3 October 2017 through 5 October 2017
ER -