TY - GEN
T1 - The 1st ACM international workshop on big data and machine learning for smart buildings and cities
AU - Dong, Bing
AU - Markovic, Romana
AU - Carlucci, Salvatore
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/11/17
Y1 - 2021/11/17
N2 - The proliferation of urban sensing, IoT, and big data in buildings, cities, and urban areas provides unprecedented opportunities for a deeper understanding of occupant behavior, transportation, and energy and water usage patterns. However, utilizing the existing data sources and modeling methods in building science to model urban scale occupant behaviors can be pretty challenging. Therefore, technological progress is needed to unlock its full potential. In order to fulfill the latter task, this workshop focuses on the methodologies for big urban and building data collection, analytics, modeling, and real-world technology deployment. The workshop aims to open discussion on the current challenges of big data in smart buildings and cities.
AB - The proliferation of urban sensing, IoT, and big data in buildings, cities, and urban areas provides unprecedented opportunities for a deeper understanding of occupant behavior, transportation, and energy and water usage patterns. However, utilizing the existing data sources and modeling methods in building science to model urban scale occupant behaviors can be pretty challenging. Therefore, technological progress is needed to unlock its full potential. In order to fulfill the latter task, this workshop focuses on the methodologies for big urban and building data collection, analytics, modeling, and real-world technology deployment. The workshop aims to open discussion on the current challenges of big data in smart buildings and cities.
KW - big data analysis
KW - digital cities
KW - machine learning
KW - modeling and prediction
KW - occupant behavior
KW - smart buildings
UR - http://www.scopus.com/inward/record.url?scp=85120984647&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85120984647&partnerID=8YFLogxK
U2 - 10.1145/3486611.3491139
DO - 10.1145/3486611.3491139
M3 - Conference contribution
AN - SCOPUS:85120984647
T3 - BuildSys 2021 - Proceedings of the 2021 ACM International Conference on Systems for Energy-Efficient Built Environments
SP - 338
EP - 340
BT - BuildSys 2021 - Proceedings of the 2021 ACM International Conference on Systems for Energy-Efficient Built Environments
PB - Association for Computing Machinery, Inc
T2 - 8th ACM International Conference on Systems for Energy-Efficient Built Environments, BuildSys 2021
Y2 - 17 November 2021 through 18 November 2021
ER -