PhD thesis public defense on "Mobile Sensor Networks for Air Quality Monitoring in Urban Settings"
Event details
| Date | 29.08.2016 |
| Hour | 17:00 |
| Speaker | Adrian Arfire |
| Location | |
| Category | Conferences - Seminars |
With urban populations rapidly increasing and millions of deaths being attributed annually to air pollution, there is a critical need for a deeper understanding of urban air quality. The locality of urban emissions sources, and the specific topography of cities lead to a very heterogeneous pollutant concentration landscape, the details of which cannot be captured by traditional monitoring stations. Although highly accurate, these systems are large, heavy and very expensive, which leads to a very sparse distribution of measurements.
Mobile sensor networks hold the potential to allow a paradigm shift in our understanding of urban air pollution, through an augmentation of the spatial resolution of measurements. The road to achieving reliable high quality information from these type of systems is, however, full of challenges. These start from the system design, as the task of developing robust mobile sensing networks for continuous urban monitoring is arduous in itself. The limitations of existing sensor technology lead to issues of signal distortion and make the task of maintaining long-term sensor calibration very difficult. Finally, the development of appropriate modeling techniques that would enable us to generate high-resolution pollution maps based on mobile sensor network data is a hard problem due to the inherently dynamic and partial coverage of such systems.
The aim of this thesis is to show the feasibility of mobile sensor networks for monitoring air quality and their ability to achieve the goal of pushing our understanding of urban air pollution. We have taken a holistic approach, by studying the end-to-end system, and addressing each of the aforementioned challenges. Using public transportation vehicles for mobility, we have developed and deployed a full-scale mobile sensor network for monitoring the air quality in the city of Lausanne, Switzerland.
Mobile sensor networks hold the potential to allow a paradigm shift in our understanding of urban air pollution, through an augmentation of the spatial resolution of measurements. The road to achieving reliable high quality information from these type of systems is, however, full of challenges. These start from the system design, as the task of developing robust mobile sensing networks for continuous urban monitoring is arduous in itself. The limitations of existing sensor technology lead to issues of signal distortion and make the task of maintaining long-term sensor calibration very difficult. Finally, the development of appropriate modeling techniques that would enable us to generate high-resolution pollution maps based on mobile sensor network data is a hard problem due to the inherently dynamic and partial coverage of such systems.
The aim of this thesis is to show the feasibility of mobile sensor networks for monitoring air quality and their ability to achieve the goal of pushing our understanding of urban air pollution. We have taken a holistic approach, by studying the end-to-end system, and addressing each of the aforementioned challenges. Using public transportation vehicles for mobility, we have developed and deployed a full-scale mobile sensor network for monitoring the air quality in the city of Lausanne, Switzerland.
Links
Practical information
- General public
- Free
Organizer
- DISAL