Temperature and Humidity Time Series of Cold Storage Room Monitoring

The datasets contain the raw data and preprocessed data (following the steps in the Jupyter Notebook) of 9 DHT22 sensors in a cold storage room. Details on how the data was gathered can be found in the publication "Towards Self-Adaptive Monitoring of Storage Environments with Distributed Sensor Systems" by Elia Henrichs, Florian Stoll, and Christian Krupitzer (in Proceedings of the 2025 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), 2025, pp. 85-90, https://doi.org/10.1109/ACSOS-C66519.2025.00033). This dataset consists of the following files: Raw.zip - The raw data CSV files of the nine Arduino-based data loggers, containing the semicolon-separated columns date (formatted as dd.mm.yyyy), time (formatted as HH:MM:SS), temperature, and humidity. These files can contain multiple headers. Preprocessed.zip - The preprocessed data CSV files of the nine Arduino-based data loggers, containing the semicolon-separated columns date (formatted as dd.mm.yyyy), time (formatted as HH:MM:SS), temperature, and humidity. Multiple headers were removed, and the length of the datasets was aligned to equal length by filling missing values with NaN. DataPreprocessing.ipynb - Jupyter Notebook containing the code to preprocess the data and create the overview file, which summarizes key characteristics of the dataset. DataPreliminaryAnalysis.ipynb - Jupyter Notebook containing the code to perform the preliminary data analysis (general statistics, peaks, and matrix profiles). experiment_actions.csv - CSV file logging performed actions (door openings and sensor movements). overview.csv - CSV file summarizing key characteristics of the dataset and preliminary data analysis. temphum_logger.ino - Source code to run the Arduino-based data logger with a sampling rate of 5 sec. Arduino_setup_sketch_v1.png - Circuit diagram of the Arduino-based data logger.