Turin, with its ToMove project, has been selected for the realisation of a Living Lab aimed at promoting the co-development and testing of new scenarios and solutions for autonomous, connected and cooperative mobility (so-called CCAM technologies) in close relation with the MaaS services that will be developed in parallel within the ‘TorinoMaaS4Italy’ project.

The project is funded by the Department for Digital Transformation as part of the PNRR (National Recovery and Resilience Plan) and is coordinated by the City of Turin in collaboration with UniTO, PoliTO and local actors such as 5T and Links.

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The course aims to prepare students for local and global challenges by reflecting on the actions needed to make the cities of the future more equitable and sustainable through technological and social innovation. The economic wellbeing and quality of life of more than half of the world’s population depend on urban and metropolitan areas, the ability to balance growth and innovation in urban areas with social needs and the mitigation of environmental risks and social inequalities, and the concern to protect and promote tangible and intangible cultural heritage for future development.

In this context, the teaching proposes an interdisciplinary approach to the most pressing urban issues, such as: mobility, energy consumption, the water cycle, digital infrastructure, the fight against economic and social inequalities, the regeneration of economic and social inequalities, the regeneration of urban spaces through the ability to reuse the material and immaterial heritage embedded in urban forms and landscapes. Methods, technologies and best practices in the development of applications for smart mobility through the internet of things, climate control and zero energy districts in the urban environment, energy communities, ecosystem services for resilient and sustainable cities through an eco-hydrological approach, new tools for representing the city and city data, methods for assessing the socio-economic impact of policies on the future of urban populations are explored. Each topic is addressed by combining a theoretical framework with laboratory and application activities related to the Turin context.

The lectures include the participation of lecturers affiliated with the FULL centre and external guests, and will explore in detail the research conducted both within the Interdepartmental Centre of the Politecnico di Torino and internationally, success stories, and the analysis of some experiments in pilot cities. The disciplinary areas involved are urban studies, planning and architecture, energy, environmental, network and electronic engineering, and geomatics. The first edition of the course ran from November 2022 to June 2023. The inaugural lecture was delivered by Chiara Foglietta, Councillor of the City of Turin for Ecological and Digital Transition, Innovation, Mobility and Transport.

The third edition is underway for 2024/25.

2022/23 Course program

INTRODUCTION

– 04/11/2022 Presentation of “100 Climate-neutral Cities by 2030,” the case of Turin (with Councilor Chiara Foglietta) + presentation of the course and exercise (Loris Servillo, Caterina Quaglio)

MODULE I/a – Physical and social infrastructure

– 11/11/2022 NZEB, Nearly zero-energy buildings (Maria Ferrara)

– 11/18/2022 Integration of renewable sources and energy communities + visit to the PVZEN laboratory – PhotoVoltaic Zero Energy Network (Enrico Fabrizio)

– 11/25/2022 How food market logistics are changing our cities (Agostino
Strina)

– 12/02/2022 The Valentino Park project (Elena Vigliocco)

– 12/16/2022 Wrap-up 1 (Loris Servillo, Caterina Quaglio)

MODULE II – Ecology and circular economy

13/01/2023 – Designing Circularity – Introduction to the Circular Economy (Elena Piera Montacchini and Silvia Tedesco)

03/03/2023 – Reuse of Rainwater (Roberto Revelli)

10/03/2023 – Water Remediation (Tiziana Tosco)

24/03/2023 – Visit to Ortialti (Elena Carmagnati)

31/03/2023 – Wrap-up 2 (Loris Servillo, Caterina Quaglio)

MODULE III – Smart and Digital

MODULE II/b – Ecology and Circular Economy

MODULE III – Smart and Digital

28/04/2023 – Mobility and Vehicle Traffic Simulation Systems (Marco Rapelli)

05/05/2023 – Visit to 5T (2:00–6:00 PM, two groups)

MODULE I/b – Physical and Social Infrastructure

-19/05/2023 – Regenerating the Existing City, Bike Tour of Case Studies in Turin (Daniele Campobenedetto)

– 26/05/2023 Wrap-up 3 (Loris Servillo, Caterina Quaglio)

(TBD) FINAL EVENT: Presentation of the work and open discussion

cover photo credit: Lucio Beltrami

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As part of the 5G-EVE project, FULL Polito is developing a vertical application of the platform, focusing on the “Smart Tourism” use case. FULL’s research therefore aims to study the potential of the infrastructure to promote new methods of accessing cultural information, based on real-time interaction with physical space—within buildings, sites, or parts of cities. This approach is based on the use of augmented reality (AR) and micro-localization technologies and aims to enrich the user experience by providing contextual information accurately related to the perceived space, on both an architectural and urban scale.

2019 was the year of extensive development of 5G technology, capable of guaranteeing access to large amounts of data at higher speeds, opening the field to new developments and possibilities. This is the context for the European 5G-EVE project (5g-eve.eu), funded by the European Community as part of the public-private partnership of H2020 projects, with the aim of creating a horizontal validation platform for extensive testing of 5th generation cellular network (5G) standards. The project develops and connects the infrastructure of various European sites (in Greece, Spain, France, and Italy) to create a single end-to-end service.

As part of the 5G-EVE project, FULL Polito is developing a vertical application of the platform, focusing on the “Smart Tourism” use case. FULL’s research therefore aims to study the potential of the infrastructure to promote new methods of accessing cultural information, based on real-time interaction with physical space—within buildings, sites, or parts of cities. This approach is based on the use of augmented reality (AR) and micro-localization technologies and aims to enrich the user experience by providing contextual information accurately related to the perceived space, on both an architectural and urban scale.

The trials are taking place in a section of Turin’s Spina 2 district that is already equipped with 5G infrastructure, specifically between the Officine Grandi Riparazioni (OGR) events center and Turin Porta Susa station.

The work involves developing a mobile app capable of requesting and receiving data from a server via the 5G network. The transmission range is exploited to obtain spatial models and large amounts of multimedia information. In addition, the edge computing capabilities of the infrastructure are used to keep the data received by the device up to date, based on the user’s location and activities, defined using GPS, AR, and other location-supporting technologies.

An initial prototype validated the app’s general features. The tool is divided into two parts relating to the two scales of information granularity: architectural and urban. The first part aims to display information about services and landmarks in the context in AR, by superimposing labels on images in open areas. At the architectural scale, and also in closed environments, the second component of the prototype uses AR to display more detailed information (theses, images and videos, structured data).

These functions were tested within the OGR area, where the AR experience was activated through the recognition of works of art. In addition, it is possible to activate a navigable 3D map with information on the services available within the facility.

Starting from this prototype, work is underway to extend the area of application to the various sites covered by the validation infrastructure (Sanpaolo Skyscraper, Porta Susa Station, Le Nuove Prison, and OGR) and to introduce additional functions. These include indoor AR navigation functions – for example, for accessing train platforms at the station – AR functions based on the tracking of three-dimensional objects through point cloud scans, virtual tour experiences with spherical images – particularly at the Le Nuove Prison museum – and access to geospatial and historical information about the urban fabric of Spina 2.

The system under construction is based on a structure with two virtual machines, the first of which enables geo-query web services that filter data and functions according to the buffer area in which the user is located, while the second hosts the geospatial database containing the files to be sent to the devices and the related metadata. The system allows the development of “lightweight” applications that, at the local level, i.e., on the physical memory of the device, maintain the minimum amount of data necessary, leaving it to the 5G structure to quickly update or stream information and ensure a smooth and rich user experience.

Finally, an automated testing system was set up to detect the KPIs (Key Performance Indicators) of the developed architecture without requiring the use of the app in the field, but using an emulator of the app itself, which reproduces its queries and receives the requested content from the server.

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Arch•i – Architectural Intelligence

The city is now producing a brand-new quality and kind of information on itself, in the form of data that can be stored, organised and analysed. Current technical needs are format standardisation, information gathering, management and selection, data processing and visualisation. This is leading to unprecedented developments of tools. New networks of relationships between documents can be defined and rapidly redefined, according to continuously updating needs and contents. In this complex information topology, the physical form of architecture maintains a key role, on which even the most up-to-date processing can be founded.

Italy has 49 cultural sites on the UNESCO World Heritage Site list. Despite this, only 0.7% of Italian GDP is allocated to culture¹. Sites such as the Imperial Fora in Rome or Pompeii and Herculaneum host millions of visitors each year, but cannot provide appropriate information services on site and face management and maintenance problems. At the same time, due to low tourist flows, many small, isolated or less well-known historical and archaeological sites cannot afford surveillance and maintenance and are thus not accessible. The available resources need to be optimised in order to ensure the protection of cultural heritage and to enhance its value.

The research project entitled Arch•i – Architectural Intelligence concerns the development of digital technologies to enhance the accessibility and management of cultural sites and the exploration of the related digital information. It is thought that mobile computing technologies can overcome the limitations of traditional information tools and allow novel interactions with monuments and works of art. The project is currently employing artificial intelligence (AI) to make data networks and digital environments accessible from the physical space.

Deep learning per l’architettura

In recent years, the diffusion of large image datasets and unprecedented computational power has boosted the development of a class of AI algorithms referred to as deep learning (DL). Among DL methods, convolutional neural networks (CNNs) have proven particularly effective in computer vision, finding applications in many disciplines. While AI is just beginning to interact with the built environment through mobile devices, heritage technologies have long been producing and exploring digital models and spatial archives. Hence, the digitalisation of cultural information offers structured and ready-to-use sources of knowledge that can be retrieved through the flexible features of AI. The interaction between DL and state-of-the-art information modelling is an opportunity to both exploit heritage databases and optimise new object recognition techniques. A specific approach to automated architecture recognition could change the way in which data on the urban environment is collected, processed and analysed, and could provide more effective ways to access data.

The Arch•i project has developed a mobile app that allows users to access data about buildings and works of art simply by pointing the camera at the object. The app is capable of connecting the real city to relevant, context-aware documents such as images, texts, maps and 3D models. It builds on original developments of CNN techniques aimed at recognising architectural features. The app is based on two main blocks of software: (1) an online, geographic-enabled database that makes it possible to upload different types of document and the related information or metadata; (2) the DL part, which is stored on the device and requires a very small amount of disk space.

The app offers an access point to a yet under-exploited network of digital information, not through a catalogue or a predefined route on a map, but just by framing the urban context through a mobile camera. A vast amount of multimedia information can be linked to the elements of a city, answering questions on how to make the newly available information easily and sustainably reachable.

I passi successivi

The Central Archaeological Area in Rome and the historical centre of Turin are the first test fields of the ‘AI guide’ developed. CNNs are, however, general models and can be trained to recognise a wide range of objects in different contexts. It is therefore planned to extend the project to other sites, covering different scales and time spans.

Further developments are also planned for the integration of the proposed AI technologies and semantic spatial databases, in order to: (1) make the system more scalable, to store online large amounts of data that can be retrieved when needed; (2) exploit the interoperability of the spatial information, i.e. connecting building information modelling (BIM) data to the environment explored through the app; (3) allow access to detailed information, i.e. performing DL recognition on the scale of building details, thus recognising monument parts or categories of constructive elements, decorations and materials.

Furthermore, we are bridging our first experiments with AI and other technologies:

• AR allows the interaction with 3D digital models and can superimpose precise spatial information layers on live images of the real environment.
• 5G cellular mobile communications will make large amounts of data immediately available, redefining location-based services and content access.
• IoT devices can enable access control and enhance on-site experience, providing cost-effective monitoring solutions which do not need the physical presence of supervising personnel.

The work carried out also points out possible connections between the virtual environment and the contemporary city. DL models could be trained to recognise building types or structural components, while the related information could integrate energy performance, structural behaviours and construction phases.

The underlying assumption of the research is that architecture has a key role in approaching technologically advanced tools. Form is a means to identify physical, observable and tangible facts and it can be used to produce shared models of the complex and multi-layered urban space. On this basis, our project intends to contribute to recognition, structuring and operational use of architectural form.

Notes

Fonte: Eurostat, Spesa totale delle amministrazioni pubbliche per “ricreazione, cultura e religione”, 2015. https://ec.europa.eu/eurostat/web/products-eurostat-news/-/DDN-20170807-1 (consultato il 26 marzo 2019)

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The Turin Digital Mobility Platform, developed by the Polytechnic University of Turin, is an online model which can be used both as a navigation system and as an info-mobility service. Connected with a GPS system, provided by FCA for the purpose of this demo, it is capable of showing the position on a map environment.

Il caso d’uso presentato alla demo 5GAA è denominato “Avviso urbano georeferenziato”.

Press

• https://www.ilmessaggero.it/economia/news/fca_5g_auto-4862761.html
• https://5gaa.org/news/5gaa-live-demos-show-c-v2x-as-a-market-reality/
• https://www.riskmanagement360.it/news/arriva-dal-5g-una-svolta-nel-risk-management-stradale/
• https://www.prnewswire.com/news-releases/5gaa-live-demos-show-c-v2x-as-a-market-reality-300958637.html
• https://motori.ilgiornale.it/tim-piattaforma-5g-al-servizio-della-sicurezza-stradale/
• https://www.corrierecomunicazioni.it/telco/5g/il-5g-di-tim-al-servizio-della-sicurezza-stradale/

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In the first part of the project, a report was drawn up on the principles on which the design of road pricing tariff tools is based, essentially focused on the concept of externalities caused by the phenomenon of urban mobility and on the mechanisms to ‘internalise’ these externalities. Subsequently, a review of the empirical evidence is proposed on the effects, effectiveness and quantitative evaluation of the application of government instruments of externalities caused by mobility, focusing in particular on pollution and congestion, following both the lenses of literature and the ‘motivations’ that drive the adoption of these policies. The report ends with a particular focus on the description of the main road pricing experiences implemented on a European scale (London, Stockholm and Milan) and on the discussion of how much these experiences may suggest to those wishing to design new hypotheses of intervention of this type.

The second part of the work is dedicated to the analysis of the current behaviour of those who, for various reasons, travel in motor vehicles that involve crossing the cordon of the Limited Traffic Zone (ZTL) in Turin. These behaviours are very varied throughout the day, including in relation to the type of people travelling.

The estimate of the request for access and transit in the ZTL’ for groups of individuals and during the various hours of the day will be more or less reliable depending on the quality of the information concerning the behaviour of those who access, stop or transit in the area. In this regard, the available information largely refers to precise data relating to a few more or less significant days. It was therefore not possible to measure the reliability of the estimates that follow, with respect to which we have only a few qualitative confirmations available.

Once the volumes of journeys by purpose, distribution over time and type of individual were best estimated, it was possible to identify a series of scenarios in which different reactions are associated to the introduction of the access tariff, and consequently to attribute an effect to each scenario in terms of congestion, emissions and revenues. The information available did not allow a ‘forecast of future demand’ in the strict sense, an exercise that, however, proved to be limited in terms of effectiveness even in the previous experiences narrated in the scientific literature. For this reason, it was considered appropriate to compose plausible scenarios in which different elasticities of demand emerge. The result is an assessment of reasonable upper and lower limits for changes in demand. Which scenario will then be realised depends on many variables, in many cases completely unpredictable and in part not yet determined, such as tariffs, methods of communicating the policy and characteristics of the offer of alternative transport solutions.

In the present study, the urban traffic simulator SUMO (Simulation of Urban Mobility) was used to analyse in detail the behaviour of the urban network and traffic in Turin after the application of new policies for access to the central area.

The map of the Municipality of Turin and its surroundings was derived from OpenStreetMap and imported into the simulator via the NETCONVERT library. Since the objective of this study is to analyse the impacts of new central area regulation policies, the following changes have been made to the map to simplify the model:

• All roads within the 2.5 km diameter circle were considered around the geometric centre of the ZTL, which we will call the Central ZTL.
• Only the main and secondary roads outside the Central ZTL, but within the Municipality of Turin, are part of the model.
• Outside the boundaries of the Municipality of Turin, only the roads of higher hierarchical level were taken into consideration (motorways, motorway links, main roads).

All the pedestrian paths, cycle paths and tracks used for trains or trams and roads closed to traffic were removed from the map.

The next step involved analysing average speeds with zero flow (the speed that on average a vehicle has on the given road in zero traffic conditions) on the roads included in the model. The data is cross-matched with the average data calculated by the Supervisor system (SV) and those made available by the Google API Distance Matrix service. From these speeds, with random logics, a maximum speed on the road was attributed, between the average speed with zero flow increased by 20% and the same speed decreased by 20%. This process made it possible to obtain a no-load speed map capable of taking into account realistic travelling speeds, which could deviate from the speed limits dictated by the Highway Code due to excess or dearth.

Once the offer model (graph) was defined, the question model was constructed. For this purpose, the OD Matrix of the SV was used for the School Day type.

In the SUMO simulation model, each vehicle randomly chooses a starting road and an arrival road within the limits, respectively, of the origin zone and the destination zone.

Once a road of origin and a destination has been defined for each vehicle, the route is chosen according to the criterion of the minimum path according to Dijkstra’s algorithm, using the road travel times as weights. However, since the routes are calculated a priori, all vehicles that have to move from one area to another will choose the same roads with minimum travel time. In this way, choices that may be excellent a priori, are no longer good in the course of the simulation. Adaptive routing has therefore been added to the model that allows vehicles stopped in the queue for a time above a set threshold to calculate an alternative route with less travel time.

In order to predict possible impacts of the policy on transportation, two scenarios have been created using the model described above. A first scenario in which the central area is accessible at all hours for everyone and a second scenario in which the area is closed all day and nobody can enter. For both scenarios, measures of travel times, average speeds and emissions were extracted and compared.

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Currently, Antonio is conducting research on how to detect and mitigate potential discriminations deriving from biases in the data and in the algorithms of decision systems.

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