Crowdsourcing high-resolution air quality sensing

This project aims at using the potential of crowdsourcing for air quality monitoring.

In 2009, the OpenSense project was launched with the objective of building a network of low-cost mobile sensors for air pollution in order to provide accurate, real-time information about air quality. In this project called CrowdSense, the scientists will leverage the results of the previous Nano-Tera project OpenSense, particularly on: mobile monitoring of air pollution, sensor and communication platforms, calibration methods, sensor data gathering and visualization, statistical modeling, activity recognition, and personalized health recommendations.

By adding the dimension of crowdsourcing and human-centric computation the project will study possibilities to incentivize users to make available states based on physical measurements, such as location, motion and pollution, through their mobile personal devices or monitoring assets that they can install in their homes or on their cars.

Using a dispersion model the scientists will compute high-resolution air pollution maps for the cities of Zurich and Lausanne. The model results will provide independent and validated information on air pollutant distributions and will thereby greatly help assessing the quality of the sensor data and their suitability to measure city-scale air pollution levels. In addition, they will study concrete applications that measure the impact of long- or medium-term exposure to air pollution on human health and evaluate the potential of crowdsourcing for providing feedbacks to users.

This research project will last 36 months and is carried out by the Distributed Intelligent Systems and Algorithms Laboratory of Prof. Alcherio Martinoli. It is supported by the Nano-Tera initiative.

Project’s page on

Principal investigator Prof. Alcherio Martinoli
Sponsor Nano-Tera
Period 2013-2016
Laboratories DISAL, LSIR
External partners CHUV–IUMSP, EMPA, ETHZ, IST
Collaboration TRACE