Code
180F0111
Duration
01 January 2012 → 30 September 2016
Funding
Regional and community funding: various
Promotor
Research disciplines
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Natural sciences
- Applied mathematics in specific fields
- Artificial intelligence
- Computer architecture and networks
- Distributed computing
- Information sciences
- Information systems
- Programming languages
- Scientific computing
- Theoretical computer science
- Visual computing
- Other information and computing sciences
-
Social sciences
- Cognitive science and intelligent systems
-
Engineering and technology
- Sustainable and environmental engineering
Keywords
mobile monitoring
Black Carbon
machine learning
urban air quality
low-cost sensors
spatial interpolation
Project description
This PhD research focuses on the development and application of an integrated methodology for air quality monitoring at a high temporal and spatial resolution. The monitoring will be performed with both high quality mobile instruments and low-cost devices, and be complemented with machine learning techniques to deal with the low-cost sensors and spatial interpolation techniques.