Data Modelling for Digital Twins in the Building Sector

Loading...
Thumbnail Image
Author (Corporation)
Publication date
2022
Typ of student thesis
Bachelor
Course of study
Type
11 - Student thesis
Editors
Editor (Corporation)
Supervisor
Parent work
Special issue
DOI of the original publication
Link
Series
Series number
Volume
Issue / Number
Pages / Duration
Patent number
Publisher / Publishing institution
Hochschule für Wirtschaft FHNW
Place of publication / Event location
Basel
Edition
Version
Programming language
Assignee
Practice partner / Client
Empa, Dübendorf
Abstract
Through the collection of data via sensors in smart buildings, value can be created by assessing the collected data, and thus derive the potential energy-saving measures, reduce water consumption, and more. Metadata exists about the sensors installed, but the Linked Metadata which would allow to easily understand the dependencies of the data collected, e.g., on the thermal level, is missing. This results in a lack of knowledge about the relationship of the data recorded, the physical location of the sensors, and what is measured in detail. Consequently, a lot of implicit expert knowledge is associated with the data.
Keywords
Subject (DDC)
Project
Event
Exhibition start date
Exhibition end date
Conference start date
Conference end date
Date of the last check
ISBN
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Review
Open access category
License
Citation
Meier, S. (2022). Data Modelling for Digital Twins in the Building Sector [Hochschule für Wirtschaft FHNW]. https://irf.fhnw.ch/handle/11654/41689