Opinion

IoT and the (overdue) rise of the machines.

Nov 15, 2019

IoT has been a promise long in the making. This time around, it may finally deliver.

The main concept behind the Internet of Things (IoT), in which devices get to exchange data signals and work complementarily with each other, is not new. Machine-to-Machine (M2M), IoT’s predecessor in the tech terminology race, has been around for over two decades now. For example, smart electricity meters (which dispense with the need for manual readings while sending consumption data straight to utility companies) amounted to about 39 million units in Europe at the end of 2008. Hardly, thus, a brand new technology for 2019.

What is novel, though, is the unique combination of factors that can catapult IoT to new levels of complexity, sophistication and adoption.”

Recent breakthroughs have thus aligned and, with seemingly perfect timing, paved the way for a step change in the IoT reality:

  • Mobile networks, the preferred mode of communications for non-static IoT devices, are advancing into a 5th generation of capabilities (5G). They will be able to handle a much higher density of devices per area of coverage, with much higher throughputs and much lower latencies than today’s 4th generations do. That will unlock, simultaneously, the combined ability to serve more IoT units, with heavier data exchanges and quicker round-trip responses between them.
  • Wi-Fi, a natural connectivity choice for static IoT devices (which do not need to move around and can be directly powered with grid electricity), is on the verge of moving to its 6th iteration, known as Wi-Fi 6. Wi-Fi 6 will be able to deliver faster throughputs, consume less energy and manage – much like 5G – a higher density of connected devices than Wi-Fi 5 currently can.
  • Information processing has shifted away from devices and into remote servers (also known as ‘the cloud’ or, when those servers are physically close to the devices they serve, ‘the edge cloud’). With that, heavy duty computations can be carried out elsewhere while still having their outputs fed into unassuming, simple devices. Voice recognition is perhaps the poster child of this fracture: humans talk to local devices and then their voice is processed, interpreted and responded to in robust cloud servers, which can then just send back to the devices the instructions on how they should ‘respond’.

Add those elements together and what you get is the ideal platform for IoT use cases to grow in scope, depth and volume. Entire verticals may be upended – or simply created from scratch – with this newly-found abundance of machine connectivity and data exchanges.

iot-infographic

Source: GSMA, Intelligence, 2018

This explosive growth presents Communications Service Providers (CSPs) with unprecedented opportunities to capture new revenue streams. From connectivity alliances with IoT vendors to state-of-the-art solutions for enterprise customers, their up-selling options are likely to be significant.

To have a shot at those opportunities, CSPs must first see and understand how the deluge of IoT devices will be connecting over their networks. Only then will they be able to capitalise on the value from the new IoT market, negotiate profitable partnerships with technology vendors and build new service offerings that can give them a genuine leg-up.

At Niometrics, we believe that much of that intelligence will come from applying network analytics onto the IoT landscape. That can give CSPs real-time and historical insights about the number of active IoT connections, the type and volume of their associated data usage, APN-based statistics, as well as key Quality of Service (QoS) analytics down to cause codes level. Marketing teams will gain a multi-perspective and complete view of the IoT ecosystem on the network, enabling them to forge strategic alliances with IoT vendors to chase new monetisation opportunities.

With all that, CSPs may ultimately aspire to go beyond offering pure connectivity while actively shaping the IoT ecosystems forming on top of their networks.

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