GreenPulse. Energy-autonomous mobile sensor system with edge computing for real-time urban environmental monitoring and prediction

About the FRIAS Project Group

Public health and environmental sustainability are significantly affected by the impacts of urban climate change, which urgently demands innovative environmental monitoring solutions. GreenPulse, as an energy-autonomous wireless sensor system, overcomes the limitations of current monitoring stations by providing high-resolution and real-time urban air quality monitoring. It is specially designed for mobile platforms like bikes and uses low-cost sensors to track spatiotemporal environmental dynamics on air pollutants, temperature and humidity. The measured raw environmental data will be first pre-processed and then transmitted via LoRa communication to generate dynamic air quality and heat maps. With the help of edge computing, real-time healthy route planning for inner-city commuting will be provided. Integrated machine learning methods will enhance accurate sensor calibration and improve predictive models of air quality for the assessment of how various urban zones behave in climate change. Therefore, GreenPulse will set a new benchmark for low-cost and high-resolution dynamic urban air quality monitoring, thereby advancing sustainable cities and climate resilience.

Period of Funding: 2026-2027

Illustration of a cyclist in an urban environment measuring air pollutants with a low-cost sensor mounted on the bicycle. The data is transmitted via LoRa communication, transformed into dynamic air quality and heat maps, and displayed on a smartphone for real-time healthy route planning. Heading: ‘GreenPulse: Urban Climate Change Monitoring’.

Project Group Members

Portrait of Wanli Yu

Dr.-Ing Wanli Yu

University of Freiburg
Internet of things (IoT), sensor networks, edge computing, embedded artificial intelligence

Member FRIAS Project Group
October 2025 – December 2026

FRIAS Project Group: GreenPulse: Energy-autonomous mobile sensor system with edge computing for real-time urban environmental monitoring and prediction

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Prof. Dr. Peter Woias

University of Freiburg

Internal Fellow (FRIAS Project Group)

FRIAS Project Group: GreenPulse: Energy-autonomous mobile sensor system with edge computing for real-time urban environmental monitoring and prediction

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Prof. Dr. Andreas Christen

University of Freiburg

Internal Fellow (FRIAS Project Group)

FRIAS Project Group: GreenPulse: Energy-autonomous mobile sensor system with edge computing for real-time urban environmental monitoring and prediction

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Prof. Spyridon Nikolaidis

University of Thessaloniki
Physics

Internal Fellow (FRIAS Project Group)

FRIAS Project Group: GreenPulse: Energy-autonomous mobile sensor system with edge computing for real-time urban environmental monitoring and prediction