Globally, transportation is responsible for about 30% of air pollution, and in large cities, this is even higher. Between 20%-40% of deaths due to serious diseases are caused by air pollution (source: https://www.stateofglobalair.org/sites/default/files/documents/2020-10/soga-global-profile-factsheet.pdf). In Spain, 10.000 people die every year due to air pollution (almost tripling traffic deaths) and in Madrid alone, there are 5000 pollution deaths per year (14/day).
The combination of mobility data (generated from anonymized and aggregated mobile phone data of the telecommunications sector), IoT pollution & climate sensor data from moving vehicles, and Open Data, can provide actionable insights about traffic mobility patterns and pollution such that authorities and policymakers can better measure, predict and manage cities’ mobility and pollution.
This micro project is strategically aligned with Europe’s Green Deal and the EU Data Strategy.
Demonstration with visualizations for pollution in Spanish city
Press release, blog post on organizations’ websites
Potentially scientific publication and patent (TBC)
- Telefónica Investigación y desarrollo S.A. (TID), Richard Benjamins
- Volkswagen AG, Richard Niestroj
- Università di Bologna (UNIBO), Laura Sartori
- Consiglio Nazionale delle Ricerche (CNR), Fosca Giannotti
Primary Contact: Richard Benjamins, Telefonica
Main results of micro project:
Air pollution is a serious problem in most cities. European regulation requires cities to not exceeding thresholds of pollutants. However, oftentimes measurements are taking place at the district level ignoring the fact that air quality might be different for every street. Moreover, air quality has not the same importance in a residential area versus a more industrial area. And the type of use is also important such as schools, hospitals, sports facilities, et cetera.
We have created a prototype, in collaboration with the city of Madrid, that exploits both privately held data as well as publicly available (open) data to monitor air quality at street level. Data sources include traffic, vegetation, temperature/windspeed and demographics. The system allows cities to perform evidence-based policy- and decision-making. This is the first of a series of three micro projects.
Contribution to the objectives of HumaneAI-net WPs
This project uses industrial data from the telecommunications industry, combined with open data and IOT generated data to solve an important societal problem, which are the two objectives of WP6. It shows a way in which the industry can create new products and services using artificial intelligence and data, very much aligned with the European data strategy. However, using data and AI for more evidence-based policy-making and decision-making by public institutions, also has ethical issues such as bias and undesired discrimination. In the prototype, we not only measure the quality of the air but also how many people are affected by this. In the series of three micro projects, we want to study whether this kind of data driven policy-making introduces undesired bias and inequality. We want to use the results of the other work packages to mitigate those potential problems.
- Program/code: Prototype – Pedro de Alarcon
- Other: Video – Roberto Valle
- : Business and government presentations – Richard Benjamins