Combining 5G IoT and mmWave: the best of both worlds

5G brings benefits not just to consumers and enterprises but also to the Internet of Things (IoT), with a number of new features being introduced to enable further enrichment of the IoT ecosystem. However, 5G doesn’t just enhance existing IoT business models, it also introduces completely new ways of obtaining data for analysis and action.

Large data transfer will shape the 5G ecosystem

Low bandwidth IoT is well catered for with existing technologies, both within the 3GPP 5G ecosystem, such as NB-IoT, and outside, such as Long Range (LoRa). These technologies are forecast to grow almost exponentially and benefit from massive IoT upgrades in 5G, which in turn support a higher density of connections.

However, at the same time as 5G is maturing, other technologies that can influence the IoT are also beginning to develop. Cloud based computing, AI and Edge computing are emerging trends that complement upgraded devices and user equipment such as 4K & 8K cameras or AGVs (autonomous guided vehicles), which independently generate large amounts of data. As such, the 5G ecosystem for IoT will not emerge exactly how it was planned, and the need to transfer large amounts of data, rather than small bits and bytes, is set to become a dominant force.

Take high resolution cameras for example. Many cameras now cost less than an equivalent 5G IoT device. While they are inherently ‘unintelligent’ devices, they can start playing a crucial role in data analytics when pointed at a piece of machinery or a perimeter fence. By enabling them to upload real-time HD or UHD video streams to the cloud for analytics, sophisticated algorithms can be employed to identify data in these images. For example, people, movement, vibrations, even temperature can be identified, meaning multiple sensors could be replaced with a single hi-res video stream.

We are already seeing scenarios where cameras allow for remote operation of machinery, such as the tracking of goods, or health and safety applications. These are driven by the use of AI and Machine Learning in the cloud, ultimately automating many tasks and enabling digital transformation of industrial processes or whole businesses.

Network deployment models are evolving

With innovative use cases that use 5G in inventive ways now emerging, it is becoming clear that the IoT will use 5G networks in different ways than first thought. It turns out that 5G IoT is more aligned with enabling broadband, high bandwidth IoT than it is in supporting narrowband IoT. With so many high bandwidth devices driving huge data volumes to be collected, 5G’s strength is in its ability to provide the low latency, high bandwidth connectivity that these devices and applications need. This goes in hand with the cloud native nature of 5G: as more data is generated, so cloud services are able to scale to meet the increased demand. This means that the capacity of the network to analyse complex IoT data and deliver new solutions and tools into vertical industries is transforming not just the IoT, but the network deployment models that go alongside them.

The role of private 5G networks

To guarantee this level of high bandwidth, low latency and good quality of service many users are turning to 5G private networks. This in turn also provides them with a level of security and control over data that public networks cannot offer. In fact, one could go so far as to say that private networks are the next evolution for Industrial IoT. They fully enable the digital transformation promised by intelligent connectivity, aligning IoT with the next generation of data rich services, such as digital twin and digital threads, giving an enterprise complete oversight and control of a products design, manufacturing, distribution, and commissioning.

Supporting these complex data models means an increasing number of use cases require significant uplink bandwidth, something known as ‘Mass Data Upload’, where there is so much data to transfer, dedicated uplink bandwidth or backhaul is required. Unlicenced mmWave spectrum is ideal for this. It allows for dedicated gigabit uplink without compromising on quality of service and is well suited to complement a full 5G private network as it can be under full ownership and control of the end customer.

Combining 5G IoT and mmWave technology is giving customers the best of both worlds: enterprises can connect and manage their assets without limitation on the amount of data generated. It also simplifies the network architecture, and it becomes viable to give full flexibility over whether to use edge or centralised cloud analytics for different applications and use cases. The denser the data generated, the more appealing this model becomes.

Get in touch with us to found out how mmWave equipment can provide the flexibility and scalability needed for innovative, dense 5G IoT networks.