Technological advances change paradigms, and the construction industry has never been a stranger to this. The BIM methodology took the development of comprehensive executive projects to another level of efficiency and interaction between the various specialties involved in a project. In this context, digital twins are gaining ground, as designers and owners have begun to understand their potential in the construction world.
A digital twin is a virtual replica of a product, environment or process that simulates the behaviour of its physical counterpart. The union of the physical and virtual worlds allows for an exhaustive analysis of the information, making it possible to monitor and analyse its actions in various situations and improve its performance. To this end, the digital twin must be a data reference that encompasses all phases of the lifecycle of the object in question, from its design and manufacture to its construction, including operational and maintenance phases and, if applicable, its reuse. Using AI, machine learning and IoT technology, the digital twin should behave like a 'living entity' that interacts with its physical twin by updating itself and preventing future problems.
A digital twin can be as complex as required, ranging from simple consumer products to complex systems such as metro networks or cities. Within the possibilities in the construction industry, a digital twin can collect data and, through it, improve the performance and manage the long-term maintenance of a building's installations (hydraulic, sanitary, electrical, etc.), thereby generating economic benefits for the owners. In the case of refurbishments, a digital twin allows us to analyse the design and response of its physical counterpart in advance, thereby reducing risks, and therefore the possibility of financial loss.
In case a project has been developed with BIM methodology, at the time of physical construction, the digital twin is generated per se, and the quality of the digital twin will be determined by the amount of information that has been poured into it. The value of this information is high, as it is dumped from a standardised environment and therefore the data captured can be reintroduced into the planning and design phases of new projects, thus applying data learning for continuous improvement.
The benefits of this methodology are not only for the development of new projects. In the case of an existing building or one that has not been developed using the BIM methodology, and therefore requires the collection of project information - which would involve additional costs - there are various methods for its collection: from the traditional way that involves physical surveys and digital capture, to technologies such as Scan to BIM, which relies on the issuance of a point cloud generated by a 3D laser scanner. This analyses the environment to take data on its shape and, through this information and specialised software, generates a digital model.
Finally, digital twins need not be isolated entities. By integrating several, designers can create connected systems that would enable information exchanges that could optimise the functioning of their physical counterparts in relation to their environment. Thinking along these lines, the potential of this technology is immense, as cities could be built that feed real-time information to their digital counterparts, which could predict or solve problems such as traffic flows, optimisation of energy consumption, analysis and improvement of security systems, and even ways to respond to natural disasters or pandemics. The ability of digital twins to collect and interpret data gives them the ability to create direct social impacts and influence the development and improvement of everything from small products to entire cities.
