Digital Twins

A digital twin is a virtual replica of a physical object, system, or process. It serves as a bridge between the physical and digital worlds, allowing for real-time monitoring, analysis, and optimization.

Digital twins are created using data from sensors installed on the physical asset. This data feeds into the virtual model, which mirrors the asset’s condition and behavior. In the industrial metaverse, digital twins are used to monitor machinery, predict maintenance needs, and improve operational efficiency.

For example, a digital twin of a wind turbine can track performance metrics, predict failures, and optimize energy output. In smart cities, digital twins model urban environments to manage resources, plan infrastructure, and enhance the quality of life for residents.

In healthcare, digital twins of patients, sometimes called virtual patients, can simulate individual responses to treatments, aiding in personalized medicine.

The use of digital twins enhances decision-making by providing insights that are not easily obtainable from the physical asset alone. It reduces downtime, lowers maintenance costs, and improves product development processes by enabling simulations and testing in the virtual realm before applying changes in the real world.