Natural nighttime ventilation and daylight-optimized shadowing are high potential approaches to efficiently and economical cool buildings. Nevertheless, the full potential cannot be acquired, since, if at all, such behavior is manually initiated by users. Goal of this project is the development of an automated, self-learning system that can assess the full cooling capabilities and establish an alternative to conventional air conditioning systems.
Details
Duration | 01/01/2018 - 31/12/2021 |
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Funding | FFG |
Program | Stadt der Zukunft |
Department | |
Principle investigator for the project (University for Continuing Education Krems) | Ass.-Prof. Dipl.-Ing. Dr. Daniela Trauninger |
Project members |
Dipl.-Ing. Wolfgang Stumpf
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