Technological & educational solutions to the issue of air pollution using a blended research approach
Initial situation

Air pollution is a fundamental problem in the Balkan region – especially in Northern Macedonia. In the World Health Organization (WHO) air pollution database, the city of Skopje is among the most polluted capitals in Europe, with particulate matter concentrations of PM10 and PM2.5 (UNEP, 2018). According to a study by Dimovska & Mladenovska (2019, p.428), air pollution has a significant impact on health and the spread of diseases in Northern Macedonia. Extreme air pollution and the increasing high risk of airborne diseases reduce the attractiveness of the region as a place to live and work.

Project idea

The CleanBREATHE collaborative project Technical & Educational Strategies to Address Air Pollution through a Blended Research Approach; Subproject: User Interface Design, Social Intervention and Citizen Participation aims to explore the impact of awareness raising strategies and the effect of mobile data collection methods disseminated through social networks. The analysis and visualisation of air quality data will raise the public’s awareness of air pollution and related problems. The CleanBREATHE project’s air pollution reduction goals are divided into 3 sub-goals:


Goal 1: Developing sensor technologies to extend the sensor networks (sensor kit) distributed by citizens. The hardware and software form the core element for AI-based prediction algorithms. The expansion of the data collection network with newly designed mobile and stationary sensors will enable the collection of regionally relevant data on air pollutants. This includes the detection of particularly strong polluters of air pollution, through the geographical collection of data and evaluation of air flows.
Goal 2: From the data, possible measures for the public, industry as well as governmental organisations will be derived. A concept for citizen participation and social intervention will be developed to bring about long-term behavioural change.
Goal 3: Developing a new business model for the sensor kit and public awareness installation.


In the CleanBREATHE project, existing solutions and new approaches for forecasting air quality are tested and further developed (prototypes) using a design science research approach. For this purpose, algorithms will be used to evaluate the data, extract air pollution characteristics and relate them to each other.
CleanBREATHE will partly use the existing infrastructure of sensors and air quality data to raise awareness of air pollution. Based on the AirCare app, the concept, design and technical implementation of such survey tools will be further developed. We use the principle of mobile crowdsensing to collect additional data. The increase in locations and time periods in which data is collected improves the reliability of forecasts. The data is visually processed for the users so that the app presents an educational added value as recommendations for action and ultimately stimulates a change in behaviour. Workshops with citizens and students will raise awareness of the topic and increase participation in the data collection. In addition, a direct transfer of knowledge about air pollution and solutions for companies will be discussed. The aim is to raise public awareness of environmental issues and ultimately reduce air pollution. In a next step, the research results will be presented to policy makers. To achieve these goals, a marketable, digital product at reasonable prices will be developed with technological components that drive particulate matter awareness.

Key data
    01.10.2021 – 31.09.2024
  • University of Applied Science Magdeburg-Stendal
  • Ss. Cyril and Methodius University in Skopije (SCMU), North Macedonia, Faculty of Computer Science (FCSE), Laboratory for Eco-Informatics
  • Business Innovation Coach
  • Federal Ministry of Education and Research (BMBF, WBC2019)
  • German Aerospace Center (DLR)

Victoria Batz, M.A.
Interaction Design
University of Applied Science Magdeburg-Stendal

Dr. Petre Lameski
Artificial intelligence
Ss. Cyril and Methodius University in Skopje

Prof. Dr. Vladimir Trajkovic
Ss. Cyril and Methodius University in Skopje

Prof. Dr. Michael A. Herzog
Business Informatics
University of Applied Science Magdeburg-Stendal