Wireless Noodle Episode 29: Predicting AI

In this week’s episode Matt looks at a new set of research from Transforma Insights on forecasting the Artificial Intelligence market, considers the value and potential of 5G RedCap, a new variant on 5G aimed specifically at IoT, and examines the growing need for smart metering given the current energy crisis. 

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An approximate transcript of the podcast is available below:

Welcome to this week’s Wireless Noodle. In this episode I want to focus on one new interesting area of research for us, that of forecasting the Artificial Intelligence market, something about which we have a unique perspective. Back to the more core stuff for us, I also take a look at 5G RedCap, a new variant on 5G aimed specifically at addressing the needs of IoT. Is it any good? Will it find a niche? And finally a look at some forecasts the team at Transforma Insights has completed recently on the smart metering market. 

Ten-fold increase in AI use by 2030

Artificial Intelligence, and all its sub-components, is one of the most intriguing and potentially transformational of the currently emerging technology areas that we track at Transforma Insights. Earlier in the year we unveiled our forecasts for how we see the trajectory of deployments, including which device types it will be deployed on, which will be the dominant use cases, and which countries and vertical sectors will see the greatest use of AI. 

How big will AI be?

Firstly a note about what we’re forecasting. When we look at AI market growth, we look at the number of instances of AI that will be deployed. Instances are the best way to understand the market growth because they paint a true picture of the importance of each use type and how they are deployed. Measuring revenue is painful. Does revenue measure the spending by companies on AI? Or the cost savings associated with it (as most AI is aimed at doing the same things cheaper? Or the total revenue associated with use cases that make use of some form of AI, even if it is only a small part of that implementation? Using revenue as the metric doesn’t really reflect how and where AI is really used. 

We analysed dozens of different use cases across all vertical sectors in every country. Based on that analysis we believe that there are currently 1.8 billion instances of AI deployed globally. By 2030 we expect this to grow to 21 billion, a more than ten-fold growth. 

IoT dominates AI instances

Of those 21 billion AI instances in 2030, around 99% will be deployed on Internet of Things (IoT) devices, a figure that doesn’t change much across the forecast period. The other device types, cloud, handsets/tablets/PCs, and edge computing nodes, will account collectively for just 1%. But we shouldn’t necessarily equate that with value. Those AI instances deployed in non-IoT devices may be individually more impactful. For instance, a chat-bot deployment in the cloud may serve millions of unique users. Contrast that with AI deployed in an autonomous vehicle which will be predominantly relevant only to the vehicle upon which it is deployed (although it will be very relevant to other nearby vehicles). 

 Consumer products will account for the vast majority of IoT AI instances. ‘AV Equipment’ such as smart TVs is the single biggest use case, along with connected cars and personal electronics. Other big ones are those related to security and public safety, including significant adoption in CCTV for the purposes of behaviour analysis and identify public safety threats. Many IoT devices, including autonomous vehicles, AR/VR devices and delivery robots, will all require some form of AI. As IoT use cases grow, so will the requirement for AI.

The Transforma Insights analysis also includes equally granular assessment of each of the other device types. For instance, cloud deployments will tend to focus on enterprise-wide requirements, dominated by two main use cases. Firstly, those related to IT security, such as identifying hacking attempts and phishing. Secondly, those associated with business efficiency such as robotic process automation, workflow optimisation and other business processes.

Where will AI see the biggest adoption?

Our numbers are built on a country-by-country basis meaning we are able to identify which countries will see the greatest adoption. China and the US will lead the way, collectively accounting for 54% of AI instances. This means that those two countries are over-indexing even relative to their shares of the global economy. 

5G RedCap: a technology without a USP

There’s been a lot of talk about how 5G can be used for IoT. In fact a lot of vendors have tried to set up 5G as the key use case for it. But, as we’ve seen with our forecasts, true high bandwidth, low latency, 5G is only really useful for a few use cases and volumes aren’t great. What we’re expecting bigger things of is NB-IoT and LTE-M, neither of which is really a 5G technology but both of which have been dragged kicking and screaming into the standard. But recently, a new variant of 5G proper has cropped up, in the form of 5G RedCap which is intended to be a low power variant of 5G new radio. But we’re sceptical at the moment. 

As a bit of background, the latest iteration of the 3GPP standards for mobile communications, Release 17, includes a new variant of 5G aimed specifically at IoT. It’s defined as ‘5G Reduced Capability NR’ (or RedCap for short), or sometimes ‘NR-Light’. It’s an interesting evolution, to try to create a lower complexity 5G New Radio device, with the intent of doing for 5G NR what LTE-M and NB-IoT did for LTE. However, with this iteration, and likely for at least a decade to come, it is highly unlikely to have a significant impact on the connectivity technology market landscape. In July 2022 we at Transforma Insights published a report entitled ‘What is 5G RedCap and how does it fit into the portfolio of cellular IoT connectivity technologies?’ which explained exactly why.

5G RedCap promises to be the 5G New Radio equivalent of the mMTC technologies NB-IoT and LTE-M, delivering on three aims. 

The first was to reduce the complexity of the devices and therefore the cost. At hundreds of dollars per module, 5G is completely out of reach of all but a very few IoT use cases. That compares to typically USD10-40 for LTE devices, depending on category, and around USD5 for NB-IoT. 5G RedCap has been somewhat successful here, recording a price reduction of perhaps 80%. 

The second aim was to reduce power consumption. To fill a useful niche RedCap needs to be capable of running of a battery. Reports are that power savings of over 90% are possible. 

The third aim was to maintain data speeds of at least those of LTE Cat-1. With speed of 85Mbit/s it comfortably does that. 

None of these capabilities really opens up a significant part of the market. What is noticeable for anyone looking closely at IoT use cases, as we do in our highly granular IoT Forecasts, is that IoT applications bifurcate, with some requiring high data rates (e.g. CCTV or connected car) and the remainder, accounting for the vast majority of use cases, needing low cost and often battery power. To put it into the terminology of 5G: IoT applications either need eMBB (enhanced Mobile Broadband) or mMTC (massive Machine Type Communications), but rarely both. And today almost nothing demands the third leg of the 5G stool, URLLC (Ultra Reliable Low Latency Communication), certainly not large scale mass-market applications. While there is ‘clear blue water’ between the capabilities of 5G RedCap and other technologies, that doesn’t mean there is a big opportunity there. 

The question is: is there demand for a mid-range technology? Our analysis suggests not. 5G Redcap ‘falls between two stools’ with middling capabilities that are not optimised for anything. 

Furthermore, it's worth noting that 5G RedCap’s main challenger is LTE Cat 4 which is both faster and cheaper, albeit that RedCap supports lower latency and a greater set of frequency bands. Fast and cheap trumps both of those capabilities, by a long way. And on the question of cost, it falls short of NB-IoT and LTE-M, by an order of magnitude. 

There is a logic to adding a lower complexity variant of 5G NR at a more cost-effective price-point, with low power consumption and superior bandwidth and latency. Ultimately, and we’re talking more than 10 years, there will be a need to support low power devices on 5G NR RAN. But for the next decade battery powered cellular IoT will be dominated by NB-IoT and LTE-M. We should note that Release 18 promises some further refinements, but they will need to be very significant to come close to the existing mMTC technologies. We expect something rather more incremental.

Energy security needs drive smart metering

We’re all only too keenly aware that the war in Ukraine is having a big knock on effect on considerations of energy supply and security. Last year 40% of the gas Europeans burned came from Russia. The war has boosted already high prices of oil and gas globally and several countries have further reduced gas imports from Russia. It has been felt perhaps most in the EU, where governments have sought to reduce consumption and shift buying away from Russia. 

For the last decade or more government in Europe has tried to reduce fuel consumption through influencing behaviour. This includes various fiscal measures such as reducing taxes on energy efficient heating systems and building insulation, and more efficient appliances and products. The use of Smart Electricity meters also plays a key role. The feedback on from smart meters on energy consumption should prompt investments by consumers in more energy-efficient technologies (such as low-energy refrigerators or freezers) as well as to encourage ‘good’ behaviour (such as switching off or reprogramming appliances). 

The other aspect of reducing energy dependence is by diversifying to renewable sources. This is particularly the case in countries that have opted to end their nuclear power programmes, such as Germany. The use of renewable energy sources for electricity drives the need for ‘load balancing’ as the supply is often highly variable. Spikes in demand typically need to be addressed using the most polluting of generating facilities, typically coal fired power-stations (or even diesel generators). Smoothing out demand, so there are fewer less pronounced peaks, will mean that less use of the most polluting energy sources. Using smart metering to monitor and even control appliances in consumer setting, and influence behaviour patterns in industry, are critical. Another example where smart meters are useful in load balancing relates to Electric Vehicles (EV) charging. Equipped with an auxiliary load control switch, meters can send on and off commands across the home area network potentially allowing the electricity supplier to schedule the time for EV charging or even draw down the battery at peak time. This in turn helps user avoid car charging at peak time. 

Back in July, Transforma Insights published our report on electricity smart metering. The report examines the reasons for the increase in installations along with detailed assessment of the progress of rollouts and the various communication technologies used across major geographies for these meters. In total there will be 2.2 billion electricity smart meters deployed by 2030, up from 814 million in 2020. The transition from traditional electricity meters to smart meters is one of the biggest IoT initiatives worldwide. 

 The arrival of new connectivity technologies will help to accelerate rollouts, as illustrated by the fact that the dominant connectivity technologies will be LPWA non-mMTC (33%) and 5G mMTC (26%) by 2030, both relatively new technology families. Although, it has to be said that this iteration of 5G RedCap is probably not going to be accounting for many of them! 

[Additional to the discussion in the podcast, a link to an article on Enterprise IoT Insights sumarising further thoughts on this topic is here]

Next week

Just a reminder: if you’re enjoying the podcast I’d be obliged if you could leave a review. It’s much appreciated. 

A quick plug now for the events we’ll be at in the next few months.

If you’ll be at Industry of Things World in Berlin, IoT Tech Expo in Amsterdam, the Things Conference in Amsterdam, Mobile World Congress Las Vegas, or IoT Tech Expo in Santa Clara, let me know. All in September/October.

Link to our events page, where we’ll be speaking, is posted on the wirelessnoodle.com page:   

Next week I’ll be talking connected cars, cloud connectors and IoT SAFE.