Data in Brief (Jun 2024)
Detailed operational building data for six office rooms in Denmark: Occupancy, indoor environment, heating, ventilation, lighting and room control monitoring with sub-hourly temporal resolution
- Simon Pommerencke Melgaard,
- Hicham Johra,
- Victor Ørsøe Nyborg,
- Anna Marszal-Pomianowska,
- Rasmus Lund Jensen,
- Christos Kantas,
- Olena Kalyanova Larsen,
- Yue Hu,
- Kirstine Meyer Frandsen,
- Tine Steen Larsen,
- Kjeld Svidt,
- Kamilla Heimar Andersen,
- Daniel Leiria,
- Markus Schaffer,
- Martin Frandsen,
- Martin Veit,
- Lene Faber Ussing,
- Søren Munch Lindhard,
- Michal Zbigniew Pomianowski,
- Lasse Rohde,
- Anders Rhiger Hansen,
- Per Kvols Heiselberg
Affiliations
- Simon Pommerencke Melgaard
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark; Corresponding author.
- Hicham Johra
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Victor Ørsøe Nyborg
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Anna Marszal-Pomianowska
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Rasmus Lund Jensen
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Christos Kantas
- Department of Architecture, Design and Media Technology, Aalborg University, Rendsburggade 14, 9000 Aalborg, Denmark
- Olena Kalyanova Larsen
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Yue Hu
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Kirstine Meyer Frandsen
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Tine Steen Larsen
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Kjeld Svidt
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Kamilla Heimar Andersen
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Daniel Leiria
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Markus Schaffer
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Martin Frandsen
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Martin Veit
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Lene Faber Ussing
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Søren Munch Lindhard
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Michal Zbigniew Pomianowski
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Lasse Rohde
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Anders Rhiger Hansen
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Per Kvols Heiselberg
- Department of the Built Environment, Aalborg University, Thomas Manns vej 23, 9220 Aalborg Øst, Denmark
- Journal volume & issue
-
Vol. 54
p. 110326
Abstract
The operational building data presented in this paper has been collected from six office rooms located in an office building (research and educational purposes) located on the main campus of Aalborg University in Denmark. The dataset consists of measurements of occupancy, indoor environmental quality, room-level and system-level heating, ventilation and lighting operation at a 5 min resolution. The indoor environmental quality and building system data were collected from the building management system. The occupancy level in each monitored room is established from the computer vision-based analysis of wall-mounted camera footage of each office. The number of people present in the room is estimated using the YOLOv5s image recognition algorithm. The present dataset can be used for occupancy analysis, indoor environmental quality investigations, machine learning, and model predictive control.
