loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Andreas Reichel ; Jens Döge ; Dirk Mayer and Jan Bräunig

Affiliation: Fraunhofer Institute of Integrated Circuits IIS, Division Engineering of Adaptive Systems EAS, Münchner Str. 16, 01187 Dresden, Germany

Keyword(s): Vision-based User Recognition, Machine Learning, Building Energy System.

Abstract: Smart Buildings enable significant savings in energy and CO2 emissions by model-predictive methods. The building users have a considerable influence on the energetic building management. On the one hand, they dictate the comfort parameters to be set. On the other hand, they generate internal thermal gains through their presence, affect humidity, consume oxygen and produce carbon dioxide. The more precisely the user behavior is known, the more precisely and resource-efficiently the room climate control can be adapted to this user behavior. In this paper, an intelligent vision-based sensor concept is proposed and tested that is capable to estimate occupancy and activity inside a building. The contribution initially concentrates on functional buildings, since here, compared to residential buildings, there is an even greater need for use-oriented room air conditioning, including savings potential.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.209.63.120

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Reichel, A.; Döge, J.; Mayer, D. and Bräunig, J. (2022). Application of AI-based Image Processing for Occupancy Monitoring in Building Energy Management. In Proceedings of the 11th International Conference on Smart Cities and Green ICT Systems - SMARTGREENS; ISBN 978-989-758-572-2; ISSN 2184-4968, SciTePress, pages 139-146. DOI: 10.5220/0011080600003203

@conference{smartgreens22,
author={Andreas Reichel. and Jens Döge. and Dirk Mayer. and Jan Bräunig.},
title={Application of AI-based Image Processing for Occupancy Monitoring in Building Energy Management},
booktitle={Proceedings of the 11th International Conference on Smart Cities and Green ICT Systems - SMARTGREENS},
year={2022},
pages={139-146},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011080600003203},
isbn={978-989-758-572-2},
issn={2184-4968},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Smart Cities and Green ICT Systems - SMARTGREENS
TI - Application of AI-based Image Processing for Occupancy Monitoring in Building Energy Management
SN - 978-989-758-572-2
IS - 2184-4968
AU - Reichel, A.
AU - Döge, J.
AU - Mayer, D.
AU - Bräunig, J.
PY - 2022
SP - 139
EP - 146
DO - 10.5220/0011080600003203
PB - SciTePress