Writing scalable building efficiency applications using normalized metadata
Author:
Affiliation:
1. University of California, Berkeley
2. University of Virginia
3. IBM TJ Watson Research Center
Funder
U.S. Department of Energy
Directorate for Computer and Information Science and Engineering
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2674061.2675031
Reference1 articles.
1. Project haystack. http://project-haystack.org/. Project haystack. http://project-haystack.org/.
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1. SeeQ: A Programming Model for Portable Data-Driven Building Applications;Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation;2023-11-15
2. A Programming Model for Portable Fault Detection and Diagnosis;Proceedings of the 14th ACM International Conference on Future Energy Systems;2023-06-16
3. Deploying data driven applications in smart buildings: Overcoming the initial onboarding barrier using machine learning;Energy and Buildings;2023-01
4. Advancing smart building readiness: Automated metadata extraction using neural language processing methods;Advances in Applied Energy;2021-08
5. Automated point mapping for building control systems: Recent advances and future research needs;Automation in Construction;2018-01
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