Franck R. Dauge

TL;DR: An exhaustive evaluation of 24 identical units of a commercial low-cost sensor platform against CEN (European Standardization Organization) reference analyzers, evaluating their measurement capability over time and a range of environmental conditions shows that their performance varies spatially and temporally.

TL;DR: The results indicate that the data fusion method provides a robust way of extracting useful information from uncertain sensor data using only a time-invariant model dataset and the knowledge contained within an entire sensor network.

TL;DR: Air-Quality Sensors Philipp Schneider,*,† Alena Bartonova,† Nuria Castell,† Franck R. Dauge,† Michel Gerboles,‡ Gayle S. Jones, Sean Khan, Alastair C. Lewis, Bas Mijling, Michael Müller, Michele Penza, Laurent Spinelle, Brian Stacey, Matthias Vogt,† Joost Wesseling, and Ronald W. Williams are authors.

TL;DR: It is demonstrated that, despite relatively low accuracy at the individual sensor level, a methodology based on geostatistical data fusion is capable of merging the information from the sensor network with model information in such a way that it can obtain realistic and frequently updated maps of urban air quality.

TL;DR: In this paper, the authors proposed a method for improving air quality and reducing carbon emissions in Oslo, a city with one of the fastest growing cities in Europe, which is recognized that air quality is a major factor for human health.