High-Resolution Indoor Environmental Dataset from a Living Lab with Personalized Environmental Control Systems (PECS)

The building sector faces growing challenges in balancing energy efficiency with occupant comfort, especially amid climate change, air pollution, and post-pandemic demands on HVAC systems. Personalized Environmental Control Systems (PECS) offer a promising solution by allowing individuals to control their immediate environment (e.g., temperature, air quality), thereby enabling energy savings without sacrificing comfort. Despite their proven benefits, PECS have seen limited market adoption due to the lack of standardized performance evaluation methods and benchmark data.

Computational Fluid Dynamics (CFD) is commonly used to study PECS, but creating accurate CFD models is resource-intensive and requires detailed experimental validation—something many researchers struggle to provide due to limited infrastructure. Currently, only one known benchmark dataset exists, which is not representative of real-world settings.

To address this gap, the current work presents a high-resolution dataset of indoor environmental measurements (air velocity, temperature, and CO₂) from a living lab designed to simulate an open-plan office. The dataset, detailed in an accompanying Excel file, supports the creation and validation of CFD models for spaces equipped with various ventilation setups, including standalone systems and PECS configurations.