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Against this background, manufacturers must bring the entire business and its employees up to speed for widespread digitization to work. If companies remain too passive, their position in the market will sooner or later be undermined. It is especially important since the experts within the organization hold the key to one of the most pressing IT concerns in the digital era: how can we process all this data in a way that truly benefits the business?

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In the manufacturing sector, the Internet of Things (IoT) and the Industrial Internet of Things (IIoT) are major digitalization drivers. And that will remain the case for the foreseeable future, especially given the imminent rollout of 5G technology in mobile networks. 5G will enable the connection of many additional devices and data sources at up to 10 Gbit/s, far beyond what is possible with conventional WAN and LAN systems. Latency in particular can be greatly reduced using 5G, which plays a crucial role in autonomous driving, for example. But innovators face a test of patience: it is likely to be several more years before truly nationwide 5G coverage is available in Germany.

Augmented reality on the rise

But this also has an impact on another technology that, despite its high potential in manufacturing, is still notoriously overlooked: augmented reality (AR) and, in particular, augmented mobility – used for example for driver assistance in production and warehouse logistics, gesture recognition, factory automation and authentication solutions. At the same time, 3D sensor cameras or even 3D reconstructions or photogrammetry (image measurement) are being deployed in more and more IoT scenarios. And thanks to computer vision technology, these processes can run in real time.

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So computers are learning to see. The machine learning algorithms and depth sensors built into today’s smartphones can scan and digitally store the precise geo-coordinates of buildings, rooms and other locations. Innovative young businesses such as Mapstar in Germany and Ubiquity6, financed by millions from start-up funds, rely on this new technology. The aim is to support increased digitization of the real world for manufacturers, to alter it virtually and make it available on demand.

Powerful data glasses that work seamlessly with conventional smartphones and tablet PCs are already available. The miniaturization of complex technology means these devices are barely distinguishable from regular sunglasses. This gives augmented mobility an additional boost. The possibilities for deploying AR in an industrial context are growing at an impressive rate, partly due to decreasing hardware costs and devices becoming smaller and easier to use. There is even talk of AR contact lenses, though they are still at an early stage of development.

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Start-ups like Mojo Vision, but also market incumbents such as Samsung, are working on state-of-the-art hardware in this domain. And the IT giants with their extensive ecosystems are also jumping on the bandwagon. Google and Facebook, for instance, have both acquired start-ups specializing in eye tracking and high-end AR devices. One such system is Oculus. Eye-movement control is an appealing and reliable alternative for production employees in loud environments who don’t always have a hand free to operate a device.

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Edge computing reduces IoT costs

For small and mid-sized businesses, IoT projects often start out small, which means that the service providers are initially slow to offer support. For them, these kind of initiatives are only profitable if they are scalable or can be rolled out across multiple regions.

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This is another reason that keeping costs down, for example by using edge computing, is crucial when building IoT applications. Currently, companies do not process even five percent of the data generated in the production environment. But keeping this data in the public cloud incurs high costs. By contrast, edge computing analyzes the data at its point of creation and makes it available on demand 'at the edge'. This approach is not only cost effective, but it also reduces latency times, as well as benefitting latency-sensitive autonomous navigation, remote monitoring, face recognition, video analysis and, crucially, augmented reality applications.

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