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Bibliographic Data

ID19563588
AuthorsIoannou Anastasios, Anastasios Ioannou (Delft University of Technology, corresponding author)
Year2018
Publication date2018-01-01
Open AccessYes
TypeARTICLE
VenueArchitecture and the Built Environment (BOOK_SERIES)
Journal identifiersISSN: 2212-3202 • E-ISSN: 2214-7233
PublisherTU Delft OPEN Publishing (PUBLISHER)
DOI10.59490/abe.2018.27.3515
OpenAlexW4388491170
LanguageEN

The broader aim of this thesis was to contribute towards a more sustainable built environment, by first looking at how to seek ways to improve the existing simulation software’s ability to predict the energy consumption of residential dwellings by identifying the most important parameters that affect energy consumption and indoor comfort, which is tightly related to energy consumption. The second aim of this study was to compare the results of both PMV and adaptive models with data obtained with the use of a sensor rich smart environment. Such environments in the residential sector are still in their infancy but improvements in information technology, sensor miniaturization, software development, and analysis techniques (such as pattern recognition methods) will result to a smarter built environment in the future

Architectural engineering · Built environment · Civil engineering · Energy consumption · Software deployment · Software engineering · Architecture and Computational Design · Building Energy and Comfort Optimization · Computer Science · Engineering · Software

Highly citedNo

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Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae