Semantic contextualization of BAS data points for scalable HVAC monitoring

Ville Kukkonen

Semantic contextualization of BAS data points for scalable HVAC monitoring

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

Abstract

Buildings account for approximately 40% of the total primary energy use in the U.S. and EU, while building systems waste a lot of energy due to poor operation and faults. Automated fault detection and diagnostics (AFDD) can be used to reduce the energy waste and ensure occupant comfort, and to support monitoring-based commissioning (MBCx). Applying the methods to existing buildings is cumbersome due to poor data labeling. Scaling the methods to account for different types of buildings requires a flexible way of mapping the data points to relevant monitoring processes. This paper proposes a novel method of using a semantic model to contextualize the data points for downstream analysis applications. The method is evaluated with application examples, and further potential applications are discussed.

Original language	English
Title of host publication	ECPPM 2021 – eWork and eBusiness in Architecture, Engineering and Construction
Editors	Vitaly Semenov, Raimar J. Scherer
Place of Publication	London
Publisher	CRC Press
Pages	320-327
Number of pages	8
Edition	1
ISBN (Electronic)	978-1-003-19147-6
ISBN (Print)	978-1-032-04328-9
Publication status	Published - 2021
MoE publication type	A4 Conference publication
Event	European Conference on Product and Process Modelling - Moscow, Russian Federation Duration: 15 Sept 2021 → 17 Sept 2021 Conference number: 13

Conference

Conference	European Conference on Product and Process Modelling
Abbreviated title	ECPPM
Country/Territory	Russian Federation
City	Moscow
Period	15/09/2021 → 17/09/2021

Cite this

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title = "Semantic contextualization of BAS data points for scalable HVAC monitoring",

abstract = "Buildings account for approximately 40% of the total primary energy use in the U.S. and EU, while building systems waste a lot of energy due to poor operation and faults. Automated fault detection and diagnostics (AFDD) can be used to reduce the energy waste and ensure occupant comfort, and to support monitoring-based commissioning (MBCx). Applying the methods to existing buildings is cumbersome due to poor data labeling. Scaling the methods to account for different types of buildings requires a flexible way of mapping the data points to relevant monitoring processes. This paper proposes a novel method of using a semantic model to contextualize the data points for downstream analysis applications. The method is evaluated with application examples, and further potential applications are discussed.",

author = "Ville Kukkonen",

year = "2021",

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isbn = "978-1-032-04328-9",

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editor = "Vitaly Semenov and Scherer, {Raimar J.}",

booktitle = "ECPPM 2021 – eWork and eBusiness in Architecture, Engineering and Construction",

publisher = "CRC Press",

address = "United States",

edition = "1",

note = "European Conference on Product and Process Modelling, ECPPM ; Conference date: 15-09-2021 Through 17-09-2021",

}

Semantic contextualization of BAS data points for scalable HVAC monitoring. / Kukkonen, Ville.
ECPPM 2021 – eWork and eBusiness in Architecture, Engineering and Construction. ed. / Vitaly Semenov; Raimar J. Scherer. 1. ed. London: CRC Press, 2021. p. 320-327.

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

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PY - 2021

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N2 - Buildings account for approximately 40% of the total primary energy use in the U.S. and EU, while building systems waste a lot of energy due to poor operation and faults. Automated fault detection and diagnostics (AFDD) can be used to reduce the energy waste and ensure occupant comfort, and to support monitoring-based commissioning (MBCx). Applying the methods to existing buildings is cumbersome due to poor data labeling. Scaling the methods to account for different types of buildings requires a flexible way of mapping the data points to relevant monitoring processes. This paper proposes a novel method of using a semantic model to contextualize the data points for downstream analysis applications. The method is evaluated with application examples, and further potential applications are discussed.

AB - Buildings account for approximately 40% of the total primary energy use in the U.S. and EU, while building systems waste a lot of energy due to poor operation and faults. Automated fault detection and diagnostics (AFDD) can be used to reduce the energy waste and ensure occupant comfort, and to support monitoring-based commissioning (MBCx). Applying the methods to existing buildings is cumbersome due to poor data labeling. Scaling the methods to account for different types of buildings requires a flexible way of mapping the data points to relevant monitoring processes. This paper proposes a novel method of using a semantic model to contextualize the data points for downstream analysis applications. The method is evaluated with application examples, and further potential applications are discussed.

UR - https://www.taylorfrancis.com/chapters/edit/10.1201/9781003191476-44/semantic-contextualization-bas-data-points-scalable-hvac-monitoring-kukkonen

M3 - Conference article in proceedings

SN - 978-1-032-04328-9

SP - 320

EP - 327

BT - ECPPM 2021 – eWork and eBusiness in Architecture, Engineering and Construction

A2 - Semenov, Vitaly

A2 - Scherer, Raimar J.

PB - CRC Press

CY - London

T2 - European Conference on Product and Process Modelling

Y2 - 15 September 2021 through 17 September 2021

ER -

Semantic contextualization of BAS data points for scalable HVAC monitoring

Abstract

Conference

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