cities – Progress in Research

Artificial intelligence for accessibility in historic centres

Posted on 20/12/202306/08/2024 by Erik Franco

Using Artificial Intelligence systems to identify, especially in historic city centres, the most accessible routes for elderly people and people with motor disabilities: this is the aim of the research work of Daniele Treccani, a young researcher at the Unesco Research Lab in Mantua of Politecnico di Milano.

The research, published in the International Journal of Applied Earth Observation and Geoinformation, used a mobile mapping system (in this specific case, a car equipped with instrument provided by Leica Geosystems Italia) for surveying and mapping the small town of Sabbioneta, which has been, together with Mantua, a UNESCO World Heritage Site since 2008 and is an emblematic example of a Renaissance village enclosed within historic walls.

Machine Learning was used to automatically detect the differences between streets and pavements made of pebbles, cobblestones and bricks, with widely varying heights and widths, which on the one hand distinguish and are typical of historical cities and on the other hand make moving difficult for people with motor disabilities. The good reliability rate of the data obtained (89%) was verified on site; this allowed using it for designing a map of the most accessible routes.

Starting from the collected data or point clouds, namely millions and millions of points distributed in the surveyed space that allow us to obtain measures and three-dimensional representations of what surrounds us, for instance houses, streets, squares, pavements and various objects, it is possible to identify, with the help of Machine Learning, the most accessible trajectories and paths in a historical urban context. The work on Sabbioneta made it possible to test and demonstrate the importance of AI methods for managing accessibility in historic city centres.
Daniele Treccani, researcher of the Department of Architecture, Built Environment and Construction Engineering

The automatic extraction of geometric and space georeferenced information can be extended to other urban elements and be used for tourism accessibility and navigation applications, as well as for the creation of map bases for Plans for the Elimination of Architectural Barriers (PEBA) or Urban Accessibility Plans. More in general, the data collected and processed can be useful for the construction of City Models and digital models of historic city centres.

Daniele Treccani is currently working on extending his research to data from other urban survey systems, such as UAS (drone) photogrammetry, laser scanner survey systems from aircrafts or with portable systems (backpacks or handheld), and continues his collaboration with the University of Vigo (Spain), with which he carried out part of the research.

Machine Learning (ML) allows a complex neural network attempting to simulate the functioning of the human brain, to “learn” from a large amount of data previously structured by an operator. After the learning phase, it is possible, through a combination of inputs, to recognise and classify objects within the data, automatically and with no human intervention.
Andrea Adami, Professor of Topography and Cartography

DESIRE – Designing the Irresistible Circular Society

Posted on 20/02/202306/08/2024 by Erik Franco

The Politecnico di Milano continues to affirm its leading role in European research with new projects in the context of the New European Bauhaus initiative, launched by the European Union to spread the culture of the European Green Deal among citizens.

DESIRE – Designing the Irresistible Circular Society, involves the Department of Design with the group led by prof. Alessandro Deserti.

This Coordinated and Support Action supports the “100 climate-neutral and smart cities” mission, proposing an approach to design that is attentive to circularity principles and open to artists, creatives, makers and other organizations. Starting from architecture, design and art, DESIRE will create an open learning environment, defined by principles, methods and guidelines that support the design of an irresistible circular society.

DESIRE is one of the six “demonstrator” projects of the New European Bauhaus initiative and will be tested in 8 urban spaces and neighbourhoods in 6 different European countries: Denmark, Italy, Latvia, Slovenia and the Netherlands.

DESIRE will work in and with these contexts, focusing on three challenges: creating of forms of inclusive housing; the “symbiotic relationship” typical of urban landscapes and the related optimization of the use of material flows; “reconciling cities with nature” for designing liveable habitats and functional ecosystems from a multispecies perspective by rebalancing land use to accommodate the generation of resources and biodiversity.

URBEM: a national database of reference buildings to assess energy saving measures

Posted on 02/12/202206/08/2024 by Erik Franco

The URBEM (Urban Reference Buildings for Energy Modelling) project is financed by the Ministry of Universities and Research (MUR) as a Project of Significant National Interest (PRIN). With participation from 10 Italian universities coordinated by professor Francesco Causone of the Politecnico di Milano’s Department of Energy, the project aims to create a national database of reference buildings to be used with UBEM (Urban Building Energy Modelling) tools capable of assessing energy saving measures for major building stocks through dynamic simulations involving several buildings simultaneously.

This database will make it possible to reduce uncertainty in results of UBEM simulations, providing a reference tool and a methodology of analysis for public authorities (and other property stock owners), who will be helped in their management of building assets, conservation activities and the promotion of policies and incentives.

In the current phase, researchers are defining and characterising the building and energy databases available at the national, regional and local levels. This will be followed by a data mining and data analysis phase and then the implementation of the reference buildings within urban-scale energy simulation software.

URBEM project website