Abstract
We present how crowdsensing with civil officers contribute to collect larger amount of urban data with high spatial-temporal coverage, and enable to understand urban features by analyzing the data. We implemented a crowdsensing system which fits to daily city management, and conducted long-term experiment with garbage section of Fujisawa city, Japan. Based on analysis of collected data, we show that our system provide fine-grained urban data compared to crowdsensing with citizens with improving efficiency of city management. In addition, we analyze our dataset with demographic urban data, and clarified the relationship between pattern of uncollectible garbage thrown and features of resident area.
| Original language | English |
|---|---|
| Title of host publication | UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 303-306 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781450359665 |
| DOIs | |
| Publication status | Published - 2018 Oct 8 |
| Event | 2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018 - Singapore, Singapore Duration: 2018 Oct 8 → 2018 Oct 12 |
Other
| Other | 2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018 |
|---|---|
| Country | Singapore |
| City | Singapore |
| Period | 18/10/8 → 18/10/12 |
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Keywords
- City Management
- Crowdsensing
- Urban Computing
- Urban Data Analysis
ASJC Scopus subject areas
- Software
- Human-Computer Interaction
- Information Systems
Cite this
Poster : Accelerating urban science by crowdsensing with civil officers. / Yonezawa, Takuro; Takeuchi, Koh; Ito, Tomotaka; Sakamura, Mina; Kishino, Yasue; Naya, Futoshi; Ueda, Naonori; Nakazawa, Jin.
UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, 2018. p. 303-306.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Poster
T2 - Accelerating urban science by crowdsensing with civil officers
AU - Yonezawa, Takuro
AU - Takeuchi, Koh
AU - Ito, Tomotaka
AU - Sakamura, Mina
AU - Kishino, Yasue
AU - Naya, Futoshi
AU - Ueda, Naonori
AU - Nakazawa, Jin
PY - 2018/10/8
Y1 - 2018/10/8
N2 - We present how crowdsensing with civil officers contribute to collect larger amount of urban data with high spatial-temporal coverage, and enable to understand urban features by analyzing the data. We implemented a crowdsensing system which fits to daily city management, and conducted long-term experiment with garbage section of Fujisawa city, Japan. Based on analysis of collected data, we show that our system provide fine-grained urban data compared to crowdsensing with citizens with improving efficiency of city management. In addition, we analyze our dataset with demographic urban data, and clarified the relationship between pattern of uncollectible garbage thrown and features of resident area.
AB - We present how crowdsensing with civil officers contribute to collect larger amount of urban data with high spatial-temporal coverage, and enable to understand urban features by analyzing the data. We implemented a crowdsensing system which fits to daily city management, and conducted long-term experiment with garbage section of Fujisawa city, Japan. Based on analysis of collected data, we show that our system provide fine-grained urban data compared to crowdsensing with citizens with improving efficiency of city management. In addition, we analyze our dataset with demographic urban data, and clarified the relationship between pattern of uncollectible garbage thrown and features of resident area.
KW - City Management
KW - Crowdsensing
KW - Urban Computing
KW - Urban Data Analysis
UR - http://www.scopus.com/inward/record.url?scp=85058339372&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85058339372&partnerID=8YFLogxK
U2 - 10.1145/3267305.3267641
DO - 10.1145/3267305.3267641
M3 - Conference contribution
AN - SCOPUS:85058339372
SP - 303
EP - 306
BT - UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers
PB - Association for Computing Machinery, Inc
ER -