5G network provides higher bandwidth, faster speed and lower latency, enabling applications such as remote fleet management and augmented reality to happen in factories. However, the applications cannot be completed by only using 5G network, but by incorporating Edge Computing, it becomes possible.5G network provides higher bandwidth, faster speed and lower latency, enabling applications such as remote fleet management and augmented reality to happen in factories. However, the applications cannot be completed by only using 5G network, but by incorporating Edge Computing, it becomes possible.
Greater bandwidth, superior speeds, and the capability to provide coverage to large-scale IoT devices make 5G the ideal connectivity technology. The benefits provided by 5G make it more suited for industrial IoT than any of the previous incarnations of connectivity technology that have come before it. Connected devices, such as sensors, vehicles and machines, have introduced a lot of new opportunities to the industrial world. Experts in a remote location can manage assets worldwide, companies can migrate from product to service sales, deliver added-value services, improve safety and become more sustainable by extending the lifetime of machines.
“The new capabilities of 5G enable a machine operator to do more, like connecting with HD video and maneuver machines remotely in real-time,” said Jon Lindén, CEO of Ekkono Solutions, a software company providing machine learning technology for IoT devices.
Case 1: Fleet management
Imagine the following context: two vendors of industrial automated machines sell their products to three manufacturers whose factories are located individually in different cities. Currently, each vendor would need one system for each factory to manage machines, causing them to manage three different systems for the same machines.
With the help of 5G networks and Edge Cloud Computing capabilities, each factory is able to create different slices for accessing data and enabling remote monitoring and controlling of industrial machines provided by various vendors. It makes it easier to control and manage products located in various factories, including studying how operations can be improved, designed and by receiving deployment updates.
Case 2: AR for troubleshooting
Augmented reality (AR) troubleshooting is an application for information sharing in the repair and maintenance area. Due to the already heavy workload for technicians, the technology aims to eliminate the need for Word documents that come with long-listed instructions.
With the help of AR, technicians are able to “see” visual instructions on an electronic board, which can be inspected, so technicians know which components need repairing and testing. It’s also time-saving, cutting out the need to switch focus between the paper document and the circuit board. In this future factory, 5G provides low latency of data transmission required for augmented image quality. Due to the high bandwidth of the network, technicians can experience high-resolution image quality without disrupting the connection between other devices.
IIoT is accomplished by 5G and edge computing
In order to achieve fully connected industrial 4.0 IIoT, with a multitude of incorporated connected IoT devices, a 5G network isn’t the only requirement, but also another technology is necessary – Edge Computing. Cloud Computing means using cloud as the main computing place. Data produced by local devices are gathered and sent to the cloud, processed in the cloud and then the results are sent back to the system. Edge Computing, on the other hand, lets computation and data storage happen closer to the local devices. In this case, cloud is mainly used to transmit data instead of computing, which will improve response time and save network bandwidth.
Industry 4.0 use cases require sub-milliseconds latencies, accurate location, high reliability and very high throughput. It’s hard to achieve the goals without the help of Edge Computing, which creates reliable local offload and backend cloud integration for real-time data processing and content localization. Ekkono, furthermore, provides “Edge Machine Learning” technology, which enables machine learning onboard the devices, making them self-learning from data and becoming predictive. When machines are smart and predictive, they will be able to make qualified decisions themselves on how to run optimally and only call for attention as needed.
“The smarts is a necessity as we cannot have 50 billion dumb devices, it’s unrealistic to manage them manually, which means that they have to become somewhat autonomous. The difference compared to a smartphone is that smartphones are constantly supervised, and the intelligence is the person operating it,” said Lindén. “5G is built for purposes to accommodate the fantastic opportunity that IoT represents, and it will accelerate and push the development forward. It removes some remaining hurdles for the real IoT potential to come true,” said Lindén.