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Title: Automated Point Mapping for Building Control Systems: Recent Advances and Future Research Needs

Abstract

This paper presents a review of recent research and development on methodologies relevant to automating mapping of points in building control systems and between building control systems and external or replacement software and hardware. Manual point mapping is labor intensive and costly, presenting a major impediment to innovations in building control (e.g., automated fault detection and diagnostics, self-healing, and automated commissioning for existing building control systems). The methods reviewed focus on classifying building control system points, especially sensor classifications by sensor type. Fewer publications address other important aspects of the point mapping problem, such as discovering spatial and functional relationships among points, relationships between control system points, physical systems, and equipment, and between various equipment and the systems of which they are part, and discovering metadata, normalizing it to a common namespace, and assigning the metadata to control system points. To motivate further development of new automated point mapping approaches, we identify many research questions organized into three key technical needs: 1) a complete solution and underlying problem formulation, 2) alignment of methods with the actual point mapping problem, and 3) test cases, data sets for testing, explicit test procedures, and consistent performance metrics for reporting testing and evaluation results.

Authors:
; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1495345
Report Number(s):
PNNL-SA-123329
Journal ID: ISSN 0926-5805
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Automation in Construction
Additional Journal Information:
Journal Volume: 85; Journal Issue: C; Journal ID: ISSN 0926-5805
Country of Publication:
United States
Language:
English
Subject:
Building automation systems, building control, machine learning, point mapping, metadata, semantics

Citation Formats

Wang, Weimin, Brambley, Michael R., Kim, Woohyun, Somasundaram, Sriram, and Stevens, Andrew J. Automated Point Mapping for Building Control Systems: Recent Advances and Future Research Needs. United States: N. p., 2018. Web. doi:10.1016/j.autcon.2017.09.013.
Wang, Weimin, Brambley, Michael R., Kim, Woohyun, Somasundaram, Sriram, & Stevens, Andrew J. Automated Point Mapping for Building Control Systems: Recent Advances and Future Research Needs. United States. doi:10.1016/j.autcon.2017.09.013.
Wang, Weimin, Brambley, Michael R., Kim, Woohyun, Somasundaram, Sriram, and Stevens, Andrew J. Mon . "Automated Point Mapping for Building Control Systems: Recent Advances and Future Research Needs". United States. doi:10.1016/j.autcon.2017.09.013.
@article{osti_1495345,
title = {Automated Point Mapping for Building Control Systems: Recent Advances and Future Research Needs},
author = {Wang, Weimin and Brambley, Michael R. and Kim, Woohyun and Somasundaram, Sriram and Stevens, Andrew J.},
abstractNote = {This paper presents a review of recent research and development on methodologies relevant to automating mapping of points in building control systems and between building control systems and external or replacement software and hardware. Manual point mapping is labor intensive and costly, presenting a major impediment to innovations in building control (e.g., automated fault detection and diagnostics, self-healing, and automated commissioning for existing building control systems). The methods reviewed focus on classifying building control system points, especially sensor classifications by sensor type. Fewer publications address other important aspects of the point mapping problem, such as discovering spatial and functional relationships among points, relationships between control system points, physical systems, and equipment, and between various equipment and the systems of which they are part, and discovering metadata, normalizing it to a common namespace, and assigning the metadata to control system points. To motivate further development of new automated point mapping approaches, we identify many research questions organized into three key technical needs: 1) a complete solution and underlying problem formulation, 2) alignment of methods with the actual point mapping problem, and 3) test cases, data sets for testing, explicit test procedures, and consistent performance metrics for reporting testing and evaluation results.},
doi = {10.1016/j.autcon.2017.09.013},
journal = {Automation in Construction},
issn = {0926-5805},
number = C,
volume = 85,
place = {United States},
year = {2018},
month = {1}
}