TY - GEN
T1 - The 15th International Workshop on Urban Computing
AU - Ruan, Sijie
AU - Zheng, Yu
AU - Liang, Yuxuan
AU - Meng, Chuishi
AU - Li, Yanhua
AU - Ye, Jieping
AU - Yu, Philip S.
N1 - Publisher Copyright:
© 2026 Owner/Author.
PY - 2026/8/8
Y1 - 2026/8/8
N2 - The unprecedented expansion of global metropolises has modernized many people's lives, yet it has also engendered significant challenges, such as air pollution, increased energy consumption, and traffic congestion. Tackling these deeply intertwined challenges was nearly impossible years ago given the complex, dynamic, and constantly shifting environments of cities. Nowadays, ubiquitous sensing technologies and distributed computing infrastructures have produced a variety of big data in urban spaces, e.g., human mobility, air quality, traffic patterns, social media, and geographical data. Motivated by the opportunities of building more intelligent cities, we came up with a vision of urban computing, which aims to unlock the power of knowledge from big and heterogeneous data collected in urban spaces and apply this powerful information to solve critical problems our cities face today, ultimately fostering sustainable ecosystems and elevating the human experience.
AB - The unprecedented expansion of global metropolises has modernized many people's lives, yet it has also engendered significant challenges, such as air pollution, increased energy consumption, and traffic congestion. Tackling these deeply intertwined challenges was nearly impossible years ago given the complex, dynamic, and constantly shifting environments of cities. Nowadays, ubiquitous sensing technologies and distributed computing infrastructures have produced a variety of big data in urban spaces, e.g., human mobility, air quality, traffic patterns, social media, and geographical data. Motivated by the opportunities of building more intelligent cities, we came up with a vision of urban computing, which aims to unlock the power of knowledge from big and heterogeneous data collected in urban spaces and apply this powerful information to solve critical problems our cities face today, ultimately fostering sustainable ecosystems and elevating the human experience.
KW - ai
KW - big data
KW - spatio-temporal data mining
KW - urban computing
UR - https://www.scopus.com/pages/publications/105051099102
U2 - 10.1145/3770855.3818254
DO - 10.1145/3770855.3818254
M3 - Conference contribution
AN - SCOPUS:105051099102
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 13433
EP - 13434
BT - KDD 2026 - Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2
PB - Association for Computing Machinery
T2 - 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, KDD 2026
Y2 - 9 August 2026 through 13 August 2026
ER -