Big data from the built environment

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Big data from the built environment. / Khan, Azam; Hornbæk, Kasper.

Proceedings of the 2nd international workshop on Research in the large. Association for Computing Machinery, 2011. p. 29-32.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Khan, A & Hornbæk, K 2011, Big data from the built environment. in Proceedings of the 2nd international workshop on Research in the large. Association for Computing Machinery, pp. 29-32, 2nd International Workshop on Research in the Large, Beijing, China, 18/09/2011. https://doi.org/10.1145/2025528.2025537

APA

Khan, A., & Hornbæk, K. (2011). Big data from the built environment. In Proceedings of the 2nd international workshop on Research in the large (pp. 29-32). Association for Computing Machinery. https://doi.org/10.1145/2025528.2025537

Vancouver

Khan A, Hornbæk K. Big data from the built environment. In Proceedings of the 2nd international workshop on Research in the large. Association for Computing Machinery. 2011. p. 29-32 https://doi.org/10.1145/2025528.2025537

Author

Khan, Azam ; Hornbæk, Kasper. / Big data from the built environment. Proceedings of the 2nd international workshop on Research in the large. Association for Computing Machinery, 2011. pp. 29-32

Bibtex

@inproceedings{545a69a9cee64762a15d7181344694c5,

title = "Big data from the built environment",

abstract = "As sensor networks in buildings continue to grow in number and heterogeneity, occupants can become empowered to better control their environment for comfort maximization and energy minimization. Since buildings are the primary consumers of energy and are the dominant cause of greenhouse gases, apps that help occupants to understand and control their interactions with a building could be extremely beneficial to society. However, the massive raw data sets that could be collected must be aggregated and visualized to be usable which presents significant data handling, information visualization, and interaction challenges. In the context of Project Dasher, a prototype building site for exploring these issues, we discuss lessons learned and challenges ahead to develop ubiquitous computing support for sustainability.",

keywords = "app, augmented reality, building information model, data aggregation, massive data sets, sustainability, app, augmented reality, building information model, data aggregationmassive data sets, sustainability",

author = "Azam Khan and Kasper Hornb{\ae}k",

year = "2011",

doi = "10.1145/2025528.2025537",

language = "English",

pages = "29--32",

booktitle = "Proceedings of the 2nd international workshop on Research in the large",

publisher = "Association for Computing Machinery",

note = "2nd International Workshop on Research in the Large, LARGE '11 ; Conference date: 18-09-2011 Through 18-09-2011",

}

RIS

TY - GEN

T1 - Big data from the built environment

AU - Khan, Azam

AU - Hornbæk, Kasper

N1 - Conference code: 2

PY - 2011

Y1 - 2011

N2 - As sensor networks in buildings continue to grow in number and heterogeneity, occupants can become empowered to better control their environment for comfort maximization and energy minimization. Since buildings are the primary consumers of energy and are the dominant cause of greenhouse gases, apps that help occupants to understand and control their interactions with a building could be extremely beneficial to society. However, the massive raw data sets that could be collected must be aggregated and visualized to be usable which presents significant data handling, information visualization, and interaction challenges. In the context of Project Dasher, a prototype building site for exploring these issues, we discuss lessons learned and challenges ahead to develop ubiquitous computing support for sustainability.

AB - As sensor networks in buildings continue to grow in number and heterogeneity, occupants can become empowered to better control their environment for comfort maximization and energy minimization. Since buildings are the primary consumers of energy and are the dominant cause of greenhouse gases, apps that help occupants to understand and control their interactions with a building could be extremely beneficial to society. However, the massive raw data sets that could be collected must be aggregated and visualized to be usable which presents significant data handling, information visualization, and interaction challenges. In the context of Project Dasher, a prototype building site for exploring these issues, we discuss lessons learned and challenges ahead to develop ubiquitous computing support for sustainability.

KW - app, augmented reality, building information model, data aggregation, massive data sets, sustainability

KW - app

KW - augmented reality

KW - building information model

KW - data aggregationmassive data sets

KW - sustainability

U2 - 10.1145/2025528.2025537

DO - 10.1145/2025528.2025537

M3 - Article in proceedings

SP - 29

EP - 32

BT - Proceedings of the 2nd international workshop on Research in the large

PB - Association for Computing Machinery

T2 - 2nd International Workshop on Research in the Large

Y2 - 18 September 2011 through 18 September 2011

ER -

ID: 37732806