Fraunhofer Institute for Electronic Nano Systems
Problem statement:
Data convey facts. Data on air quality and occupancy in public transport (ÖPNV) provides a basis for decisions on whether to ride or not, and is particularly important in light of the COVID-19 pandemic or heatwaves caused by climate change. Passengers want enough space and healthy air!
Real-time monitoring is therefore desirable. However, systems for real-time monitoring of indoor air quality and occupancy, in conjunction with precise occupancy in public transport vehicles, are neither standardly integrated nor widely available.
Project goal:
In the SenMooVe project, a sensor-based solution is being developed to continuously monitor air quality and occupancy. The collected data will be processed using AI methods to assess current and forecasted safety, and the results will be transmitted to existing IT systems of the public transport partners for communication to passengers. This significantly improved data situation will create a real-time data-based decision-making foundation for public transport users, companies, and authorities, ultimately enhancing safety in public transport. Additionally, adaptive control of ventilation and air conditioning can improve sustainability in public transport.
Implementation:
The project partners will collaboratively develop a suitable, cost-effective, and easily retrofittable sensor concept (measuring particles, CO2, humidity and air pressure, temperature, volatile organic compounds, occupancy, and passenger type).
Based on this concept, data will initially be collected during pilot operations, and AI models for data processing and sensor reduction will be developed. Real-time data and forecasts for air quality and occupancy will be prototypically integrated into the existing information system after further development of the public transport information system and evaluated in a friendly user test.
