Il Digital Twin it is a paradigm that is revolutionizing governance and urban planning models. When we talk about Digital Twin we are not referring to a specific software or platform but to an ecosystem of technologies and data that allows the creation of a digital twin of a physical objectsuch as a territory, a city, a building or a work of art, but also a scenario that concerns an event or a phenomenon of the city.
The concept of Digital Twin
Unlike simple three-dimensional representations, the twin (as the word itself says) is an exact copy, a faithful representation with centimeter or millimetric precision, depending on the type of sensors used for the survey. A precise copy, therefore measurable; a myriad of geometric primitives geolocalized in three dimensions (x, y and z) that make up the 3D reproduction of the detected object.
Not just images, then, but data. With all the potential and value that data can create, also thanks to artificial intelligence. In the case of a digital scenario (let’s consider as an example the current digital twin for the event of the departure of the Tour de France from Florence), it is a question of a set of geographic databasesbig data and anything else that may be useful to represent the event, evaluate the interference this creates in the city and best manage the logistical and organizational aspects.
Applications of the digital twin in municipal administrations
The first result of using the digital twin is a new way of working for employees technical offices. The speed with which surveys and measurements can be carried out from one’s own workstation is far quicker and more efficient than sending teams of technicians directly to the site, avoiding unnecessary risks, supply and use of particular PPE, technical and economic inconveniences for the installation of scaffolding in the case of height measurements and downtimes due, quite simply, to adverse weather conditions, traffic or the need for permits and authorizations to enter closed places or limited traffic areas. A digital twin is always available, 24/7 from your workstation, even at a long distance from the physical object you are working on.
In addition to static elements, detected with very high precision laser sensors or with other acquisition techniques, the digital twin can be enriched with further data coming from both internal databases and management systems of the Municipality, and dynamically acquired by IoT sensors, so as to make the digital representation “alive” with real-time information on mobility, air pollution, noise, flows of people, weather, etc. A real big data, that is a high-volume data collectionvariability and update speed which, combined with Machine Learning and Artificial Intelligence algorithms, offers very precise elements of support for decisions (Control Room) and planning of large events and allows you to experiment with forecasting and scenario simulation models “what if” (e.g. what would happen if I changed this area or if I closed the road in this stretch).
The experience of the Municipality of Florence
Thanks to fondi PON Metro 2014-2020 and REACT (REACT-EU-FESR)the Municipality of Florence contributed to the development of open source platforms already in use, acquired new tools and carried out numerous surveys to create the digital twin of the City.
In the year 2023, a new LIDAR and aerophotogrammetric flight (with density of laspoint of at least 20 points per m2. and orthorectified multispectral images with geometric precision of 5 cm on the ground, far superior to satellite surveys), some flights with drones in particular for architectural works (Torrino di Santa Rosa, Stibbert Museum) and surveys of public green areas also in multispectral mode, the celerimetric survey and the street survey with a photographic sensor and laser scanner mounted on a car to obtain 3D scanning of the facades and streets of the city, as well as numerous projects for the deployment of IoT sensors (smart irrigation, anonymous people counting, smart parking ).
All this is in the context of a digital ecosystem that also deals with Big Data, for the benefit of the Technical Directorates and the Smart City Control Roomin which personnel from the Tramway and Mobility Directorates, the Municipal Police and utilities monitor the city in real time and share experiences and areas of action to implement corrective actions in emergencies and to plan strategic interventions also medium-long term.
The ecosystem and all the tools were presented in an event dedicated to the Municipality Management and the actors of Digital Florence on 27 February 2024. An event that sparked big interest and has stimulated the diffusion of these innovative tools to change the working methods and make them more efficient and more economical, saving both on the design times and on the costs of conducting surveys in the field.
The prospects for the immediate future
The Digital Twin, even before being a visual representation of the physical twin, is a huge georeferenced database very rich in information. For this reason, it is particularly suitable for analysis using Artificial Intelligence. AI applications on the Digital Twin of a city or territory are extremely interesting. Among the main ones we can list:
- Object recognition and cataloging: AI is able to recognize and catalog many types of objects, including trees, advertising systems, road signs, pedestrian crossings, signs, road surface types, bodies of water
- Fight against tax evasion and illegal activity: AI is able to identify dehors, terraces, swimming pools and driveways and compare the data with those present in the municipal management databases, so as to promptly identify those registered and those not registered, making checks much quicker and more effective.
- Urban planning: AI applied to the Digital Twin can be used to simulate urban development and evaluate the impact of infrastructure projects, new constructions or changes in the distribution of public services.
- Energy efficiency and environmental sustainability: by crossing data on the layout of roofs, plants and parking lots with measurements from environmental sensors and heat islands, AI is able to simulate corrective measures and new scenarios for greater environmental sustainability
- Traffic: through data from environmental and traffic sensors, city cartography, traffic directions, speed limits, reserved lanes and ordinances, AI is able to create predictive models to simulate road closures or traffic diversions , recalculating both the new flow of vehicles and the air and noise pollution in the areas affected by the change
- Public Services and Quality of Life: Thanks to the contribution of data from participating companies and sub-services, combined with data collected by the Municipality, AI can analyze and optimize the distribution of public services such as transportation, street lighting, waste collection and maintenance of roads and parks.
- Citizenship participation in public life: Through the sharing of interactive tools, maps and models that can be navigated from your PC or smartphone, it will be possible for citizens to actively participate in the ideas and simulations of future scenarios (e.g. new roads, new green areas, redevelopment of urban spaces), reducing the misinformation gap. and encouraging participation, with a view to Open-Government, in an even more immediate manner than so-called “open data”.
The Digital Twin to Redesign Urban Spaces
The Digital Twin is a powerful tool capable of revolutionizing the organizational models of planning, design and monitoring of urban spaces. Its use for Municipalities allows not only to make the management of the city more efficient and economical, but above all to base choices on objective dataalso immediately viewable, without the need for interpolation by technicians or statisticians.
Each laser survey (lidar flights, drone surveys, terrestrial surveys) constitutes a mine of very useful information and does not lose its value over time, indeed, it allows comparative analyses between the various scans made over the years, so as to make the differences evident, both through human analysis and with the help of Artificial Intelligence. Each of the millions or billions of points that constitute the survey is georeferenced and therefore perfectly superimposable on the previous one.
The time dimension becomes the fourth dimension of analysis, in addition to spatial ones. In a very simple way it is possible to “go back in time”, reason in a comparative way or make Artificial Intelligence algorithms learn the evolution between the various layers to build predictive models.
Furthermore, the sensor data, being collected in real time, helps to complete the representation with dynamic and always updated elements.
Data and findings that can also be shared with the subsidiaries, with other local bodies or with research institutes and universities, creating a real data space territorial, with a view to mutually enriching the information assets with the same costs incurred.
Conclusions
In a world increasingly driven by data, every investment in this sense feeds a real digital granary, from which to draw to support the transition towards data-driven governance.
