Journal article
Evaluation of data imputation approaches for multi-stream building systems data1
Science & technology for the built environment, v 30(8), pp 1035-1048
13 Sep 2024
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Increasing advancements in building digitization, smart sensing, and metering technologies have allowed large amounts of timeseries data to be collected for monitoring, analyzing, and controlling building systems. However, due to sensor or communication failures, the data collected are often incomplete and poor in quality. Data imputation approaches to replace the missing values, specifically based on either statistical or predictive models have been widely adopted for multivariate datasets in other domains. It is hence of interest to find an effective way to impute timeseries data collected from a building system. In this paper, we evaluate multiple data imputation approaches using data collected from a medium sized building situated in Stockholm, Sweden and a small commercial building from the ASHRAE RP-1312 research project. Sensors with widely varying characteristics from the case study buildings were selected to evaluate the imputation methods. The imputation accuracy and the impact of each chosen imputation method on information entropy, short-term building forecasting model performance, and fault detection strategy were evaluated. Results demonstrate that incorporating time-lagged cross correlations within a k-nearest neighbor (kNN) model provide the most accurate imputations without affecting the quality of subsequent data analysis.
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Details
- Title
- Evaluation of data imputation approaches for multi-stream building systems data1
- Creators
- Ojas Pradhan - Drexel UniversityJin Wen - Drexel UniversityDavid Halleberg - KTH Royal Institute of TechnologyZhelun Chen - Drexel UniversityNoresh Varman - Drexel UniversityJiajing Huang - Arizona State UniversityTeresa Wu - Arizona State UniversityK. Selcuk Candan - Arizona State UniversityZheng O'Neill - Texas A&M Univ, J Mike Walker 66 Dept Mech Engn, College Stn, TX USA
- Publication Details
- Science & technology for the built environment, v 30(8), pp 1035-1048
- Publisher
- Taylor & Francis
- Number of pages
- 14
- Grant note
- National Science Foundation; National Science Foundation (NSF)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:001230087500001
- Scopus ID
- 2-s2.0-85193812711
- Other Identifier
- 991021960649104721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Construction & Building Technology
- Engineering, Mechanical
- Thermodynamics