Digital twins can be defined as a virtual representation of an object or system designed to reflect a real-world object accurately. It’s the creation of virtual replicas of physical systems and its presentation through immersive technologies. Its main goal is that the dynamics or impact of real-world change can be simulated in a cheap, powerful and flexible way within the computational laboratory.
They can range from a simple virtual interpretation of a product component to a dynamic representation of the lifecycle activities and assets within a building or even an entire city. They can be updated from real-time data and use simulations, machine learning and reasoning to help make decisions.
Digital twins are also designed to enable a two-way flow of information. This continuous data exchange, combined with the significant analytical capability of modern computers, allows digital twins to monitor issues from a far wider vantage point than standard simulations, with greater potential to improve outcomes.
What are the main innovations that digital twins bring to the table?
Digital twins enable humans to interpret data effectively; is the most natural way for humans to understand complex data. Through techniques such as data visualization, modeling and simulation, and natural language processing, digital twins can create a virtual environment that resembles the physical system it replicates, making it highly intuitive and relatable for humans to interact with. That way, individuals are empowered to make informed decisions based on complex data.
In addition, digital twins can integrate real-time data streams from sensors, devices and simulations throughout a cityscape. This dynamic connection means they reflect the latest state of the system. When there is a change in the physical or ‘real’ system, it’s accurately reflected in real-time.
Predictive analysis is also a very relevant characteristic. The techniques used vary from machine learning, predictive analytics and optimization and they enable digital twins to simulate real-world scenarios, predict outcomes and provide actionable insights with often higher levels of precision compared to humans. With the simulation of scenarios, policymakers can explore the potential impact of any action; as they can take more creative and informed choices with less errors.
Collaborative data exploration and knowledge sharing among multidisciplinary teams are also fostered. Through a common platform to interact with data, stakeholders can collaborate, exchange insights and collectively work towards sustainable solutions. This shared understanding strengthens the human-data connection, fostering collective intelligence and driving innovation.
Where can we apply Digital Twins?
Although there are a lot of areas where it can be applied, there are some where they can be really transformative.
In Urbanism, for example. Digital twins provide a comprehensive understanding of systems, facilitate predictive analytics, optimize resource management, enhance collaboration, simulate sustainable innovations and foster public engagement. By leveraging digital twins, city officials could make more informed decisions, optimize resource utilization and work toward a more sustainable future. In that sense, in construction, digital twins can be used to simulate the construction process, optimize design, detect potential problems, and monitor the building’s performance throughout its lifecycle.
The features can also be transformative in the fields of engineering and medicine. As they be multidimensional or cross-sectoral and operate in a fully autonomous fashion, they can model complex physical entities; this can be applied in elements such as human organs, bridges and airplane engines.
