Context Presentation

Only a few fixed stations monitor air pollution at the urban scale, where it shows huge variation in space and time. However, the advent of low cost and miniaturized sensors paves the way to mobile sensor networks and crowdsensing systems. Bikes as a carrying platform seems promising: 1) distance tracks are longer than walking, 2) their embedded generator (dynamo) allows to create an autonomous energy system, 3) they do not pollute (and therefore do not distort data collection) and can both cover road network and pedestrian areas 4) human-carried measurement reinforces spatial coverage of the most frequented, hence the most important, areas. We instantiate it as CLUE: Cycle-based Laboratory of Urban Evolutions.

Auto-calibration of the sensor fleet and algorithms tolerant to erroneous measurements thanks to data density are two ways to face the low quality of the sensors (low accuracy, time drifting). Another challenge is keeping user privacy while sharing data without compromising their interpretability (for air pollution, human mobility).


Figure: CLUE embedded system

Scientific Goals

- equip a fleet of bicycles with a set of sensors

- collect information on mobility and air pollution

- merge the data of several sensors in a real environment and validate predictive models of pollutants used in aerology


Distributed sensing system, human-centered measurement tool, big data, air pollution


Christophe Bertero <>Jean-Francois Léon <>Matthieu Roy <>, Gilles Tredan <>