Abstract
Industry 4.0 is encouraging the introduction of pioneering technologies even in the construction industry. Along with the development of high technology, such as augmented reality, virtual reality, and cloud computing, the development of digital twin has been growing. This contribution aims to present the potential of digital twin in the construction field, suggesting a framework that outlines the many different possible applications in construction, with reference to school buildings. First, it summarizes the current overview of digital twin applications in building construction. Then it shows that significant steps that are being taken beyond the digital model, even if the implementation of the digital twin concept in its full meaning is still a long way off. The research is moving in this direction and the evolution of the current state of the art, combined with the experience gained in the industrial sector, will soon bring a new revolution in the construction industry.
TopIntroduction
Recently, new paradigms and technologies have been introduced in the construction sector since the term “Smart Building” entered the digital building revolution. First, the Digital Twin that integrates systems such as Artificial Intelligence (AI) and Automatic Learning (ML) to connect data, algorithms and context. Actually, deriving the definition from El Saddik (El Saddik, 2018) who wrote “A digital twin is a digital replica of a living or non-living physical entity. By bridging the physical and the virtual world, data is transmitted seamlessly allowing the virtual entity to exist simultaneously with the physical entity.” the Digital Twin in the AEC industry is configured as a virtual replica of the building, which shows in real time, through the virtual model, what happens in the physical environment. This is possible thanks to the use of sensors distributed in the environment that process the signals, elaborate them through analytical techniques and use them to simulate use scenarios or to simulate reactions to the real situation.
A rapidly growing technology is the Internet of Things (IoT) paradigm, which is paving the way for Smart Cities and Smart Buildings. The IoT has allowed to break down the data barrier between vertical domains on which the traditional ICT system was based, allowing the exchange of information between different application domains. The definition of a common model of web-based protocols for data exchange allows to transfer this data between objects, making the various parts of a network interactive.
This is where the Digital Twin concept was born, which is a candidate to revolutionize the building management model through predictive analysis and dynamic simulations based on real-time data. In the world of construction, digital models are now part of common practice, Building Information Modeling (BIM) has pioneered the virtual modeling of buildings and, in the most frontier applications, has touched, in part, the Digital Twin.
Traditionally Digital Twin was referred only to a part of the system (a turbine, an engine, etc.); Currently, thanks mainly to the Internet of Things development, they have become much more complex and are able to connect asset systems. This increasing complexity allows to combine asset data with process data, increasing the ability to solve complex problems. The last frontier is to associate data coming from people, from users, creating so-called Smart Buildings.
By optimizing systems and connecting people, owners and managers can use the Digital Twin to control the way environments are used, reduce costs, accordingly, improve occupancy rates and thus increase the overall value of the public good. In order to maximize the effectiveness of Digital Twin, you need a correct setting of high-performance databases and advanced machine learning algorithms. More generally, four key components are needed: data, algorithms, KPIs and context.
This contribution aims to present the potential of Digital Twin in the field of construction, suggesting a framework that outlines the different possible applications in the building sector, with reference to school buildings.
Key Terms in this Chapter
Digital Twin Aggregate (DTA): A DTA is an aggregate of many DTIs. The DTIs may be co-located within one entity (e.g., 100 motors in a single factory) or across entities (e.g., 100 motors across 25 factories). It is well-established a group behavior is not the sum of individual behavior. Likewise, in the future, DTAs might reveal unknown and unexpected insights.
Digital Twin Prototype (DTP): DTP is the prototype of the physical asset. It's like a recipe for creating an asset. The prototypes, dependent on the situation, will contain information pertaining to the physical attributes, properties, operating parameters, bill of materials, part numbers and more.
Digital Model (DM): A Digital Model is a digital representation of an existing or planned physical object that does not use any form of automated data exchange between the physical object and the digital object. The digital representation might include a more or less comprehensive description of the physical object.
Digital Twin Instance (DTI): A DTI (created from the DTP) is the twin of a physical asset. The DTI stays linked to the physical asset through its lifecycle. The DTI, typically, contains data relating to in-use conditions as captured through the sensors, historical state, predicted state, asset and warranty information, service records, etc. While a DTI starts with the baseline information from its prototype, over the course of the lifecycle, the DTI gets enriched with operational data.
Digital Shadow (DS): Based on the definition of a Digital Model, if there further exists an automated one-way data flow between the state of an existing physical object and a digital object, one might refer to such a combination as Digital Shadow. A change in state of the physical object leads to a change of state in the digital object, but not vice versa.