Integrating AI, Radar Technology, and Environmental Quality Sensors for Health and Energy-Aware Indoor Environments

The building sector makes a significant contribution to the advance of climate change. 36% of all GHG emissions in the EU come from the buildings sector (European Commission (2020): Energy Efficiency in buildings, no date), with healthcare facilities in particular being comparatively energy intensive. On average across OECD countries, the healthcare system is the largest CO2 emitter among all service sectors. (Climate Fund (2019): First time survey: healthcare system's carbon footprint substantial). Key research question: how it is possible to best match indoor environments to people while reducing building energy consumption? Technological advances (e.g., IoT technologies) now allow easy measurement of indoor climate (temperature, humidity, CO2 levels, etc.). However, the main influencing factor on energy consumption remains actual building use. Accurate presence detection of people (occupancy) in the building to control heating and cooling demand is only expensive and complex to implement. In parallel, the necessary vital sign monitoring (heart rate, respiratory rate, heart rate variability (HRV)) of patients, residents of nursing homes, etc. via electrocardiogram systems (ECG) or blood pressure monitors is location-bound, cost-intensive and, due to the current setting, cannot be integrated into the building technology to ensure a comfortable indoor climate. Key Message: Research into new technologies (radar sensor for contactless vital sign monitoring), combined with IoT measurement of control variables relevant to building services (room temperature, humidity, CO2 content, occupancy) and application of artificial intelligence for data analysis creates technically new possibilities for the efficient and health-promoting operation of hospitals, nursing homes or retirement homes. Intelligent health monitoring based on this allows empirical, individualized information transfer for health-promoting, climate-friendly behavior of vulnerable groups and personnel.

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01.01.2024 - 31.12.2026

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Technische Universität Graz

Universität Graz
DiLT Analytics