As connected devices--anything from the computer built into a car or a fitness wearable to a smart gas meter or wind turbine--have become cheaper to manufacture, their use has grown rapidly. Some form of connected device or system is now in almost every industry and sector. This proliferation means that traditional maintenance models requiring engineers to have easy physical access to real-world devices and systems are often no longer viable. As such, the need for an alternative management model is growing, which is where "digital twin" AI technology has enormous potential for any enterprise doing business through connected devices. This report looks at the benefits companies can gain from digital twin technology, the options available on the market to take advantage of it, where digital twins are already in use, and what some industries stand to lose by ignoring this AI trend.

The rise of computer vision has given us robot chefs and cameras that detect gas flares in fuel production. It's also led to an increase in connected cameras that are trying to run at the edge of the network. "Running at the edge" means these cameras are not only communicating wirelessly with the cloud but also communicating with local gateways and working with built-in logic boards to complete a task. The task might be as simple as notifying a manufacturer when a production line produces a defective item or as complex as identifying a person to determine if the system should sound an alarm. But as we connect more cameras and ask them to perform more complicated tasks, their fundamental architecture is changing.