This is the official repository that presents the dataset from the following paper:

Nadine von Frankenberg, Patrick Ruoff, Bernd Bruegge, and Vivian Loftness. 2020. LATEST: a learning-based automated thermal environment control system. In Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers (UbiComp-ISWC '20). Association for Computing Machinery, New York, NY, USA, 573–579. DOI:https://doi.org/10.1145/3410530.3414591

LATEST: Occupant-Thermal-Comfort-Data-Set

This module provides the data set collected in a case study for validating the LATEST system described in LATEST.

File Descriptions

• raw_data_from_influxdb_to_csv.ipynb was applied to create the main data sets. It imports setup.py, which uses the files in series/. The only cleaning that takes place is time step fitting and interchanging manual fixes due technical circumstances, such as sensor exchanges. Also, long periods in which no participant was at their workstation were removed.

• data_collection_phase.csv and temperature_control_phase.csv contain the main data sets. The former is used for training models which were deployed for collecting the latter.

• latest.names contains a description of the data sets and their features.

• preprocessed_data/U#_preprocessed_data.csv contains the fully preprocessed data per occupant, which was used for training the models for the temperature control phase.

• conda_env.yml shows the conda environment used for the project.