How to implement Public-Private-People Partnerships for intelligent air-quality monitoring. Deploying IoT, Big Data and AI in City of Helsinki and globally.

Andrew Rebeiro-Hargrave
University of Helsinki

Joel Takala
University of Helsinki

Background and Objectives
Nine out of ten people now breathe polluted air, which kills 7 million people every year. Air pollution is hard to escape, no matter how rich an area you live in. It is all around us. In Helsinki, air pollution comes from three sources: transport exhaust, seasonal street dust, and burning of wood at homes. Air quality varies due to weather and season changes. Currently, there are no good indicators for residents on how their specific behavior contributes to air quality, nor information on the local-level air quality to help them adjust their behavior to the current situation, which is a challenge in every European city. The concentration of air pollutants (gas and particle size) varies in minutes according to emission source, wind direction, weather conditions and sinks and this not reflected by current air quality monitoring schemes.

The solutions to air quality challenges are to deploy 5G architecture with massive IoT (low-cost sensors placed in every street and building) and open data for business development; to move from high-quality measurements to very individualized approach and bring together aspects of joint development and urban planning. Introducing rapid visualization of real-time air quality and emissions data in an understandable format, such as clean air navigation tools, will fuel the change, and finally, introduce best practices in healthy city planning models.

The MegaSense programme established by the University of Helsinki in 2017, enables solutions by gathering and fusing spatially variable gas and particulate measurements from high-end scientific instruments, commercial air quality transmitters, dense low-cost sensor arrays, and consumer wearables utilizing 4G and 5G technologies. MegaSense platform analytics extract properties and attributes from the data, and following Artificial Intelligence based calibration, efficiently creates accurate and predictive knowledge structures. The knowledge structures provide evidence-based representations of pollution hot spots and can be used to intervene with harmful emission events and monitor the consequences of government policy interventions.

The goal of the MegaSense consortium of research and industry partners led by the University of Helsinki is to co-innovate research ideas, products and services and improve the architecture of air quality monitoring. The MegaSense partners work together to develop 5G and secure Finnish leadership.

The objectives of the MegaSense are to increase knowledge, revenue, and growth of consortium partners and stakeholders by laying the foundations for intelligent air quality monitoring in Finland, and replicating the best practices gained in international city projects. The realization of the objectives is based on the following measures:

• Improving the capabilities of low-cost air quality sensing devices;
• Improving the quality of spatial representation of air quality sensing networks in urban areas;
• Improving the public authority intervention process of urban air quality monitoring.