This repository contains indoor temperature time-series data collected from various office rooms located in Bremen, Germany. All monitored rooms have a South or South-West facing window orientation. The data can be freely used for research, analysis, and other projects, provided that the original author is credited.
The dataset comprises measurements from four separate office rooms. To capture a realistic spectrum of indoor climates, the exact spatial placement of the sensors varies across these rooms.
- Some sensors are positioned closer to the windows, making them more susceptible to direct solar radiation and draft.
- Other sensors are located further inside the rooms, reflecting the ambient core temperature of the office.
The temperature measurements were collected using DS18B20 temperature sensors connected to ESP8266 microcontrollers. Each microcontroller was flashed with the open-source Tasmota firmware. Data points were generally sampled and recorded at a one-minute interval. The data transmission pipeline utilized standard Wi-Fi to send the readings via the MQTT protocol to an InfluxDB time-series database, with Grafana serving as the primary monitoring and visualization tool. This repository contains an export directly from the influx database.
The datasets are provided in plain CSV (Comma-Separated Values) format.
Each file contains the following two columns:
- Time: The timestamp of the measurement in UTC (Zulu time, e.g.,
YYYY-MM-DDThh:mm:ssZ). - Temperature: The recorded indoor temperature in degrees Celsius (°C).
The dataset consists of four files, each representing a different office/sensor location:
| Filename | Start Date | End Date |
|---|---|---|
South_2.csv |
2023-01-17 | 2026-03-19 |
South_5.csv |
2023-01-17 | 2024-01-12 |
South_8.csv |
2022-11-25 | 2026-03-20 |
South_9.csv |
2023-01-17 | 2026-03-19 |
Please note that these are real-world sensor measurements. The datasets may contain gaps (missing data points) due to sensor maintenance, power outages, or network connectivity issues during the recording periods. Users of this dataset should account for these missing values in their data processing pipelines.
You will find some handy scripts in tools and some example graph created from these csvs in img.
Jens Dede
Sustainable Communication Networks
University of BremenAuthor Email: jd@comnets.uni-bremen.de
Developer team Email: cn.dev@comnets.uni-bremen.de
This dataset is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License.
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
For the full legal code, please see: LICENSE or https://creativecommons.org/licenses/by/4.0/