What does a livable city look like?

Today, we are at a crucial moment for urbanism as a result of both the technological context, the new era of mass information (big data, open data, IoT) and a greater desire for transparency and participation on the part of all agents involved in urban planning and design processes.

In this context, the Mercè project embodies a new line of research that applies novel machine learning techniques (one of the branches of artificial intelligence) to the disciplines of urban planning, geography, sociology, economics and urban health with the goal of building objective knowledge and open data about urban environments.

Mercè is a citizen science experiment that involves citizens in training an algorithm to help us design more livable cities. The experiment (carried out from May to November 2020) compiled evaluations for more than 3,000 streets, and more than 42,000 total interactions were collected.

The final report compiles the results of the experiment and determines which streets in the city are most and least livable based on variables that have been individualized through a citizen voting process.

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