A virtual model of a physical object, process, or system that is updated with real-world data to simulate and predict its behavior.
A digital twin mirrors something real, such as a jet engine, a wind turbine, a factory floor, or even a whole city. Sensors on the physical asset feed data into the virtual model, keeping the two in sync.
Engineers use digital twins to monitor performance, test changes safely, and predict when parts will need maintenance before they fail. For example, a manufacturer might simulate a new production line layout in its digital twin before moving any machines. In healthcare, researchers are exploring patient-specific twins to model how treatments might work. Building a useful twin requires reliable sensor data, good physical models, and often machine learning to fill in the gaps.
The network of physical devices, from home appliances to industrial sensors, that connect to the internet to collect and share data.
LidarLight Detection and Ranging: a sensing method that measures distances with laser pulses to build detailed 3D maps of surroundings.
Smart GridAn electricity network that uses digital sensors, communication, and automation to balance supply and demand more efficiently.
VR, AR and mixed reality explained in plain English, with the devices behind each and real consumer and workplace uses so you can tell which one fits your needs.
Project management apps, digital takeoffs, drones, BIM and AI are changing how contractors bid, build, bill and keep crews safe, and what clients see along the way.
Connected sensors, digital twins and predictive maintenance are turning factories into data-driven systems. Here is a practical guide to what works and how to start without a massive budget.