The DIM Approach for Digital Twin

The DIM Approach for Digital Twin

Matteo Del Giudice
DOI: 10.4018/978-1-7998-7091-3.ch008
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In the era of connections and information and communication technologies, the building industry is facing the challenge of digitization at the building and urban scale. Several researches have been carried out to generate virtual city models to manage and represent a variety of data to reach the smart city concept. Therefore, the development of building/urban digital twins is directly linked to the definition of innovative methods and tools that are able to collect, organize, query heterogeneous data to make it available for the various involved actors. This chapter aims at presenting the district information modelling methodology that is strictly related to the digital twin concept, starting with data domains, arriving at the various tools developed to reach the users' needs.
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The city has always been considered as a meeting place where a series of complex dynamics linked to human beings' habits take place. From this point of view, it can be considered a living organism that transforms itself into the function of the society that inhabits it (Pagani & Chiesa, 2017). Vice versa, the population adapts itself to the city in which it lives, assuming behaviors that could change in another city according to its characteristics. The urban transformations that have taken place over the centuries have been driven both by the growing needs of citizens and by the technological innovation that has developed throughout history.

Over the centuries, the management of the city has been subjected to the needs of the population, which in different forms modified the urban ecosystem to improve the usability of space and optimize human activities, finding answers to the need for transformation and urban renewal according to the lifestyle of citizens and the adopted technologies.

These transformations have been often influenced by the demographic, industrial, and economic growth of countries, ignoring the aspects related to the sustainability of interventions, thus developing not very resilient cities to climate change and exceptional events caused by land degradation.

However, in recent years, more attention has been paid to the capacity of cities and buildings to adapt to climate and socio-economic change by setting several constraints to be respected on environmental sustainability.

In this sense, the EPBD directive refers to Smart Ready Technologies (SRT) which should be disseminated in the existing building stock to achieve significant energy savings with a consequent economic gain, while helping to improve indoor thermal comfort so that the building can adapt its energy behavior considering the user's needs.

Key Terms in this Chapter

Digital Twin: It is a virtual replica of reality and contains three main parts: physical products in real space, virtual products in virtual space, and the connections of data and information that ties the virtual and real products together.

Smart City: It is a place where traditional networks and services are made more efficient with the use of digital and telecommunication technologies for the benefit of its inhabitants and business. A smart city goes beyond the use of information and communication technologies (ICTs) for better resource use and less emissions. It means smarter urban transport networks, upgraded water supply and waste disposal facilities and more efficient ways to light and heat buildings. It also means a more interactive and responsive city administration, safer public spaces and meeting the needs of an ageing population.

Building Information Model: It is data rich, object oriented, intelligent and parametric digital representation of the facility, from which views and appropriate data for various users’ needs con be extracted and analyzed to generate information that can be used to make decisions and improve the process of delivering the facility.

Middleware: It represents a set of computer programs whose objective is to enable communication and management of data in distributed application. For instance, sensors for energy monitoring communicate with each other using their own computer languages, often created or implemented by different manufacturers. Consequently, the middleware works as a translator, thus allowing the sensors to communicate with each other.

Interoperability: It is defined as the ability of two or more systems or components to exchange information and to use the information that has been exchanged.

District Information Modelling: It extends the Building Information Modelling at the district scale, by creating a new kind of domain. The main challenge to face when creating a DIM concerns the ability to manage a big amount of data, coming from different domains. In this field, interoperability plays a key role for data exchange among different domains. It can be considered a first step to optimize data management and the development of a smart city.

Data Visualization: Is the graphical representation of information necessary for the understanding of technical details. In this way, by means of visual elements such as dashboards, web sites, Head Mounted Display, tables, data visualization maps help understanding and allow to hypothesize improvement scenarios.

Building Information Modelling: It is a method based on a building model containing any information about the construction. In addition to 3D object-based models, it contains information about specifications, building elements specifications, economy, and programs.

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