The CleanBREATHE project researches the impact of awareness-raising and (mobile) crowdsensing strategies to change the perception of air quality issues and investigate action by the general public, the industry, and government organizations. Expanding the air pollution sensor network through newly designed and engineered mobile and stationary sensors will allow us to collect more granular and locally relevant data on air pollutants. This will include geospatial and air-movement related data points on high-level polluters. Data visualization will be effectuated through Pulse.Eco, a crowdsourcing platform that gathers and visualizes environmental data and the mobile app AirCare. We will explore how an intuitive user interface and additional service increase the informational and educational value of web services and mobile solutions. Emphasis will be placed on actionable strategies by individuals to increase air quality and the impact of individual ownership of air quality measurement devices. Awareness of air quality parameters (AQI) needs to become a key element in public awareness of the environment similar to weather data with the significant difference that air quality can be changed through individual and community action.

CleanBREATHE seeks to improve existing approaches for the application of Machine Learning Algorithms based on feature extraction in air pollution prediction. Our new experiments investigating the combination of meteorological data and the air pollution measurement data using Convolutional Neural Networks look promising for applications like AirCare.

CleanBREATHE will use a partially existing infrastructure of sensors, data management, and air quality data to approach the awareness of air pollution. From a technical point of view, we will develop new concepts based on the existing AirCare app, its services, and its design. Moreover, through new mobile sensors, we use mobile crowdsensing (MCS) (Boubiche et al., 2019) to collect additional data with higher relevancy, and due to widespread distribution can rely on improved data availability. We then combine the technical perspective with an educational dimension and visualize the data in a way that app users actually learn and eventually change their behavior. In this context, citizen awareness will also be increased through our Critical Design Science Approach.

Following this, we will organize workshops for citizens and students to raise awareness on the topic and increase participation in the data collection process. Among local workshops, we plan to conduct joint workshops with students from Germany and N. Macedonia, using the perspective of young scientists to enhance the usability of the app and create further ideas for the research. Also, a direct transfer of knowledge about air pollution and solutions for companies will be discussed. This should lead to increased public awareness of environmental issues and, ultimately in reduced air pollution. In the next step, the results of the research will be presented to policymakers.

We aim to adjust marketable technological components and develop respectable pricing models for adaptable solutions like the Pollution Awareness App. In this context, we include our network of industry and SME partners, business innovators as well as citizens that contribute their specialist knowledge and experience to develop coherent business models, which will create new employment opportunities along with better living and working conditions.

Goal 1 aims to understand how we can create citizen awareness and behavioral changes around air pollution using a Critical Design Science Approach and explain which types of citizen participation are suitable to communicate the topic.

Goal 2 Designing and planning of sensor network extensions through crowd driven sensors that increase awareness and involvement and provide the hardware foundation for our new mobile sensing approaches and AI prediction algorithms.

Goal 3 focuses on the development of new business models from the designed artifacts that will create added value to the users and evoke environment-conscious behavior.