DOI: 10.5281/zenodo.10761326
title: Dataset of room-level indoor environmental quality measurements and occupancy ground truth for five residential apartments in Denmark

description: This dataset (.csv file) contains room-level measurements of indoor environmental quality (IEQ) variables together with occupancy ground truth for five residential apartments in Denmark over 7 days during January 2023, with a temporal resolution of 15 minutes. The occupancy ground truth has been determined based on activity logbooks filled in by apartments’ occupants. The measured IEQ variables are:



          Indoor CO2 concentration

          Indoor operative temperature

          Indoor relative humidity


Additional features were generated from those three variables: variable transforms representing the short-term dynamics of the indoor environment for each of the three IEQ variables:



          Difference between current variable value and average over the last hour

          Difference between current variable value and previous recording (15 minutes prior)

          Average of the variable over the last hour


Moreover, metadata parameters include the apartment number (1-5), room number (1-16), room type number, one-hot-encoded room type, floor area of the room, hour of the day, day number of the week, day number of the year, day label (unique identifier of a day for the different rooms) and date and time stamp. The occupancy ground truth variable is a binary 0 (no occupancy in the room) or 1 (occupancy in the room).

The full list of data variables with header name and description is as follows:



         datetime: Date and time stamp in the format DD-MM-YY HH:MM (Day-Month-Year Hour:Minute)

          indoor_co2_concentration: Indoor CO2 concentration inside the corresponding room (in ppm: parts per million)

          indoor_operative_temperature: Indoor operative temperature inside the corresponding room (in Celsius degrees)

          indoor_relative_humidity: Indoor relative humidity inside the corresponding room (in percent)

          current_value_minus_average_last_hour_co2: Difference between the current indoor CO2 concentration inside the corresponding room and the average indoor CO2 concentration over the last hour (in ppm: parts per million)

          current_value_minus_average_last_hour_operative_temperature: Difference between the current indoor operative temperature inside the corresponding room and the average indoor operative temperature over the last hour (in Celsius degrees)

          current_value_minus_average_last_hour_relative_humidity: Difference between the current indoor relative humidity inside the corresponding room and the average indoor relative humidity over the last hour (in percent)

          average_co2_last_hour: Average indoor CO2 concentration inside the corresponding room over the last hour (in ppm: parts per million)

          average_operative_temperature_last_hour: Average indoor operative temperature inside the corresponding room over the last hour (in Celsius degrees)

          average_relative_humidity_last_hour: Average indoor relative humidity inside the corresponding room over the last hour (in percent)

          current_value_minus_last_15_min_co2: Difference between the current indoor CO2 concentration inside the corresponding room and the indoor CO2 concentration 15 minutes before (in ppm: parts per million)

          current_value_minus_last_15_min_operative_temperature: Difference between the current indoor operative temperature inside the corresponding room and the indoor operative temperature 15 minutes before (in Celsius degrees)

          current_value_minus_last_15_min_relative_humidity: Difference between the current indoor relative humidity inside the corresponding room and the indoor relative humidity 15 minutes before (in percent)

          room_number: Room number label (from 1 to 16)

          kitchen: One-hot-encoded room type for kitchen rooms

          livingroom: One-hot-encoded room type for living rooms

          bedroom: One-hot-encoded room type for bedrooms

          office: One-hot-encoded room type for office rooms

          kitchen_livingroom: One-hot-encoded room type for kitchen/living rooms

          hour_of_the_day: Hour of the day (from 0 to 23)

          day_number_of_the_week: Day number label of the week (from 1 to 7)

          day_of_year: Day number label of year (from 30 to 37)

          day_label: Day number label as a unique identifier of a day for the different rooms (from 0 to 112)

          occupancy_ground_truth: Ground truth value of occupancy in the corresponding room. Binary variable taking the value of 0 when there is no occupancy (no people) in the room or 1 when there is occupancy (at least one person) in the room

          floor_area: Surface floor area of the corresponding room (in square meters)

          apartment_number: Apartment number label (from 1 to 5)

          room_type: Type of the corresponding room (kitchen, living room, bedroom, office or kitchen_livingroom)


 

A detailed description of the study case building can be found in a dedicated technical report: Kamilla Heimar Andersen, Anna Marszal-Pomianowska, Henrik N. Knudsen, Hicham Johra, Simon Pommerencke Melgaard, Marc Zein Dahl, Patrick Andersen Hundevad, Per Kvols Heiselberg (2023). Room-based Indoor Environment Measurements and Occupancy Ground Truth Datasets from Five Residential Apartments in a Nordic Climate. DCE Technical Reports No. 318. Aalborg University, Department of the Built Environment. https://doi.org/10.54337/aau550646548.

This dataset was used to develop and validate an occupancy detection XGBoost model using IEQ measurements as inputs for residential buildings during the winter period: K.H. Andersen, H. Johra, M. Schaffer, A. Marszal-Pomianowska, H.N. Knudsen, P.K. Heiselberg, W. O'Brien (2024). Exploring occupant detection model generalizability for residential buildings using supervised learning with IEQ sensors. Building and Environment, 111319. https://doi.org/10.1016/j.buildenv.2024.111319.