There is very little knowledge on the occupant actual hot water comfort (temperature and flow), usage practice, and routines (temporal and spatial distribution of hot water usage in a household). This paper describes the results from the total and hot water measurements in two Danish detached houses. The results show that, at the draw-off points, the temperature of 55 °C is never asked by the occupants, not even in the kitchen sink. The domestic water temperature differentiates depending on the function of the draw-off point, with the shower and kitchen taps being most energy- and water-intense. They constitute around 90% of the hot water use in the house. Shower units on average demand for highest temperature (i.e., 35.5 °C to 40.4 °C). Hand washing operates, on average, at temperature between 20.5 °C to 26.5 °C. Average water temperature at the taps located in utility room varies between 23 °C to 26 °C. These in-depth insight in the total and hot water use in two new-built low energy houses, can a) help building professionals designing more efficient hot water installations; b) enhance the research work on energy flexibility buildings by providing knowledge on most energy-intensive draw-off points; and c) facilitate district heating professionals in improving the network performance.

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.

A growing focus on occupant comfort, health and wellbeing has resulted in attempts to quantify indoor environmental quality (IEQ) and to determine the relative contributions of single IEQ aspects to an overall IEQ index. The recently developed IV20 tool assesses potential IEQ to label overall IEQ, and assign separate scores for the main indoor environment (IE) areas: thermal, visual, acoustic and air quality. In the absence of objective, universally applicable IEQ weights, this paper develops and executes a methodology asking regional experts with different backgrounds to make relative comparisons between related IE aspects. The authors hypothesize that wide-ranging subjective evaluations can be combined into useful relative weights (best operational solution based on the current status of IE literature). This paper presents results from an IE expert survey on relative IE aspect weights using simple percentile prioritization and the Analytic Hierarchy Process pairwise comparison. Results are compared to expert panel judgements to ensure validity. The advantages of this combined weight determination method are (1) that the expert survey ensures a broad spectrum of opinions and allows for input from different built environment disciplines, and (2) that the expert panel has tool-specific insight, methodology awareness and state of the art knowledge.