Parallel Intelligence in Semantic Digital Twins: An Interactive Decision-Support System for Indoor Comfort

Alex J.A. Donkers; Jelle N.A. van Midden; Dujuan Yang

doi:10.1109/DTPI55838.2022.9998960

Parallel Intelligence in Semantic Digital Twins: An Interactive Decision-Support System for Indoor Comfort

Alex J.A. Donkers, Jelle N.A. van Midden, Dujuan Yang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

Abstract

While buildings should be designed for their occupants, many buildings fail to satisfy their expectations. The growing research body on personal comfort models is promising to reduce the gap between perceived and predicted comfort; however, measuring perceived comfort levels, integrating them with other heterogeneous information, and making decisions based on the integrated data is a challenge. This paper combines semantic web technologies with an interactive dashboard to measure and integrate the occupants' feedback on indoor comfort. A personal comfort model then calculates an individual's preferred indoor climate. The system is tested in a case study with two occupants and shows that the digital twin can use the human-machine interaction to improve decision-making.

Original language	English
Title of host publication	2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence, DTPI 2022
Publisher	IEEE Press
Pages	159-164
Number of pages	6
ISBN (Electronic)	9781665492270
DOIs	https://doi.org/10.1109/DTPI55838.2022.9998960
Publication status	Published - 2022
Event	2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) - Boston & Ningbo, Boston , United States Duration: 24 Oct 2022 → 28 Oct 2022

Conference

Conference	2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)
Abbreviated title	DTPI2022
Country/Territory	United States
City	Boston
Period	24/10/22 → 28/10/22

Keywords

Digital Twin
Indoor Comfort
Linked Data
Personal Comfort Model
Semantic Web Technologies

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/DTPI55838.2022.9998960

Cite this

@inproceedings{e18a674f3b794bb5b1ce7a8e791be4fb,

title = "Parallel Intelligence in Semantic Digital Twins: An Interactive Decision-Support System for Indoor Comfort",

abstract = "While buildings should be designed for their occupants, many buildings fail to satisfy their expectations. The growing research body on personal comfort models is promising to reduce the gap between perceived and predicted comfort; however, measuring perceived comfort levels, integrating them with other heterogeneous information, and making decisions based on the integrated data is a challenge. This paper combines semantic web technologies with an interactive dashboard to measure and integrate the occupants' feedback on indoor comfort. A personal comfort model then calculates an individual's preferred indoor climate. The system is tested in a case study with two occupants and shows that the digital twin can use the human-machine interaction to improve decision-making.",

keywords = "Digital Twins, Linked Data, Semantic Web Technologies, Personal Comfort Model, Indoor Comfort, Digital Twin, Indoor Comfort, Linked Data, Personal Comfort Model, Semantic Web Technologies",

author = "Donkers, {Alex J.A.} and {van Midden}, {Jelle N.A.} and Dujuan Yang",

year = "2022",

doi = "10.1109/DTPI55838.2022.9998960",

language = "English",

pages = "159--164",

booktitle = "2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence, DTPI 2022",

publisher = "IEEE Press",

note = "2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)<br/> ; Conference date: 24-10-2022 Through 28-10-2022",

}

Donkers, AJA, van Midden, JNA & Yang, D 2022, Parallel Intelligence in Semantic Digital Twins: An Interactive Decision-Support System for Indoor Comfort. in 2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence, DTPI 2022. IEEE Press, pp. 159-164, 2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)
, Boston , United States, 24/10/22. https://doi.org/10.1109/DTPI55838.2022.9998960

Parallel Intelligence in Semantic Digital Twins: An Interactive Decision-Support System for Indoor Comfort. / Donkers, Alex J.A.; van Midden, Jelle N.A.; Yang, Dujuan.
2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence, DTPI 2022. IEEE Press, 2022. p. 159-164.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Parallel Intelligence in Semantic Digital Twins: An Interactive Decision-Support System for Indoor Comfort

AU - Donkers, Alex J.A.

AU - van Midden, Jelle N.A.

AU - Yang, Dujuan

PY - 2022

Y1 - 2022

N2 - While buildings should be designed for their occupants, many buildings fail to satisfy their expectations. The growing research body on personal comfort models is promising to reduce the gap between perceived and predicted comfort; however, measuring perceived comfort levels, integrating them with other heterogeneous information, and making decisions based on the integrated data is a challenge. This paper combines semantic web technologies with an interactive dashboard to measure and integrate the occupants' feedback on indoor comfort. A personal comfort model then calculates an individual's preferred indoor climate. The system is tested in a case study with two occupants and shows that the digital twin can use the human-machine interaction to improve decision-making.

AB - While buildings should be designed for their occupants, many buildings fail to satisfy their expectations. The growing research body on personal comfort models is promising to reduce the gap between perceived and predicted comfort; however, measuring perceived comfort levels, integrating them with other heterogeneous information, and making decisions based on the integrated data is a challenge. This paper combines semantic web technologies with an interactive dashboard to measure and integrate the occupants' feedback on indoor comfort. A personal comfort model then calculates an individual's preferred indoor climate. The system is tested in a case study with two occupants and shows that the digital twin can use the human-machine interaction to improve decision-making.

KW - Digital Twins

KW - Linked Data

KW - Semantic Web Technologies

KW - Personal Comfort Model

KW - Indoor Comfort

KW - Digital Twin

KW - Indoor Comfort

KW - Linked Data

KW - Personal Comfort Model

KW - Semantic Web Technologies

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U2 - 10.1109/DTPI55838.2022.9998960

DO - 10.1109/DTPI55838.2022.9998960

M3 - Conference contribution

SP - 159

EP - 164

BT - 2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence, DTPI 2022

PB - IEEE Press

T2 - 2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)<br/>

Y2 - 24 October 2022 through 28 October 2022

ER -

Parallel Intelligence in Semantic Digital Twins: An Interactive Decision-Support System for Indoor Comfort

Abstract

Conference

Keywords

UN SDGs

Access to Document

Other files and links

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TKI PPS Smart Two BWK38: enabling technologies for next generation networks for smart cities

Cite this

Parallel Intelligence in Semantic Digital Twins: An Interactive Decision-Support System for Indoor Comfort

Abstract

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Projects

TKI PPS Smart Two BWK38: enabling technologies for next generation networks for smart cities

Cite this