heatGuide provides technical solutions suitable for widespread use in private households to reduce the physiological heat load in indoor spaces. A prototype of a heat warning and management system for individual houses or rooms is developed and tested in real applications. Based on room-specific computer models and predictive algorithms as well as low-cost standard IT components for evaluating the indoor climate, the system will warn occupants of particularly stressful situations early on and provide practical instructions via an intuitive user interface. In apartments and buildings with SmartHome systems, these should also be able to be implemented automatically. The technological core is formed by reliable room-specific predictions of physiological heat stress. For these, proven building-type-based urban climate models (top-down approach) are to be combined with models for building physics, systems engineering and user behavior, which are parameterized on a room-specific basis using local, continuous measurements and self-learning AI algorithms (bottom-up approach).

Funding Institution

Baden-Württemberg Foundation

Project Duration

July 2021 – June 2024

Project Leads

Prof. Dr. Rainer Gasper, Prof. Dr. Pfafferott, Prof. Dr. Michael Schmidt (all INES)

External Partners

Projekthaus Ulm, SAIA, Mondas, Regionale Energieagentur Ulm, Stadtwerke Ulm/Neu-Ulm Netze, Robert Bosch School Ulm