DDR – Data Driven Retrofit

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Duration /
2019–2021

Funding /
Innosuisse / Swiss National Science Foundation

A/S Team /
C. Deb, M. Frei, A. Schlueter

Selected Publications /
1 / M. Frei, C. Deb, R. Stadler, Z. Nagy, A. Schlueter. "Wireless sensor network for estimating building performance," in: Automation in Construction 111 (2020): 103043. DOI Research Collection


Buildings use about 40% of the global energy and can last for over 100 years. Hence, retrofitting of buildings is essential and holds great potential to contribute to the global energy and carbon challenge. Due to estimation errors before and after the retrofit, the emission and energy reduction potential is often overestimated.

To address this issue, the A/S Research Team is developing a data-​driven building retrofit process. A custom wireless sensor network (WSN) is developed for this project. The WSN is used to assess the thermal building performance. The collected data is used to calibrate building models. These building models can then be used to explore optimal retrofit solutions for the particular building.

This project aims for researching and developing a process for time and cost-​optimal retrofit of buildings based on measured data.

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VILLE – Virtual Neighborhood Load Emulation