Svetlana Grant, IoT Programme Director, GSMA
2017 was the year IoT really started to materialise. The last 12 months built on the foundational work of the previous year, and saw deployments begin in earnest across the world – bringing IoT out of the realm of theory and experiment, and making it instead a visible feature of contemporary life. Whether in home appliances, utilities, vehicles or smart cities, the Internet of Things is now a tangible reality for millions of people.
2017 was not, however, the year IoT yielded mass returns for all those who have taken us this far – that task lies ahead. In 2018 we pave the way for the global mass market in IoT, and realise the commercial gains which will bring about its explosive potential for growth. Much of the industry’s focus will now therefore turn to the three main challenges facing it: increasing global coverage, improving cybersecurity, and enhancing the capabilities of AI and data analytics. IoT devices, services and networks will need global scale to be successful – scaling the IoT itself becomes the next frontier for the industry in 2018.
Coverage
LPWA has been key to connecting a vast array of previously standalone devices and objects. For instance, last year it supported delivery of reliable energy to remote communities, connected livestock for remote monitoring, and improvements to efficiency in industrial services. The proliferation of LPWA connections over 2017 also brought much anticipated smart city innovations to life, making day-to-day activities more efficient and convenient for citizens around the world.
It was perhaps inevitable that this process would play out first in municipal and business contexts, where investment funding is generally apportioned on a longer-term basis than in mass market product sales. By the end of 2018 however, with LPWA now very much on its way, we can expect to see rapid uptake in consumer markets, bringing an explosion of connected home appliances and wearables. The GSMA will drive global coverage of Mobile IoT networks and ensure the ecosystem reaches maturity before this explosion of LPWA devices occurs. Mobile IoT, the most reliable and secure form of LPWA connectivity, is now commercially available on more than 30 networks, which are available in more than 20 countries; in 2018, the latter will double, ensuring global availability of secure, interoperable, standards-based solutions.
As IoT deployments continue over the coming year, improving cybersecurity will be a key priority for those offering them. After a year of intensive media focus on data breaches and hacking, early adopters will seek to build confidence among investors and the public by forming new partnerships to protect against future attacks. Cisco’s Maciej Kranz points to several high-profile distributed denial of service attacks, which he believes have served as a wake-up call: “there’s a widespread recognition that not enough has been done thus far, so 2018 needs to be the year in which the threat landscape is tackled head-on.” We can therefore expect to see a rise in investment in cybersecurity among manufacturers of IoT devices and those who deploy them. There are already welcome signs of work being done to this end in relation to manufacturing, automotive and smart cities, and Mr Kranz sees cause for optimism: “I think 2018 will be a watershed year for IoT, where we move to a new phase in which IoT gains momentum as barriers and challenges are addressed, in terms of security market structures, industry standards and so on.”
Collaboration will prove essential for ensuring IoT security: end-to-end, multi-layer security will be required to protect each connected device, and it will take many partnerships between communication providers, device manufacturers, application developers, and cloud providers to make this happen. The IoT security market will therefore grow rapidly over the course of the year; Telefonica its total value will reach around $150bn by the end of the year. Mobile operators are emerging as trusted partners in the IoT security market, and in 2018 they will continue cooperating with other key players to harden IoT networks and platforms.
Capability
As the number of IoT devices grows rapidly over the coming year, communication between them will generate a previously unthinkable quantity of data. In its raw, unstructured form, this data is of limited value to anyone, and current analytics tools will be simply unable to cope. We can therefore expect to see a growing convergence between the IoT, data analytics and artificial intelligence over 2018, aimed at achieving more value from this IoT data. Sophisticated use cases, such as preventative maintenance applications for vehicles and machinery, will require greater accuracy than is possible from today’s solutions. These will be further enhanced by data securely collected in real- or near real-time from mobile networks.
IoT data, where it can be coordinated effectively, is set to become a bankable asset. The Economist famously said last year that data is the new oil; this can only be true where that increasingly voluminous data is in the hands of those who can make commercial sense of it. “People say data is the new oil, but the truth is it’s crude, unrefined”, says Brett Hurt, founder of analytics company data.world. Simply aggregating and consolidating that data is no longer a solution – there will be simply too much of it to assess manually. This means that – as companies seek to monetise that data effectively – much of the resulting growth will take place among “the enabling companies which collect, process, analyse and move data”, according to Tom Riley, manager of Axa Framlington’s Robotech fund. The market for AI, big data and business analytics is therefore set to grow to around $210bn by 2020. Two years from now, according to analysts at IDC Futurescape, 40 percent of digital transformation initiatives will leverage AI; by 2021, at least 50 percent of industrial robots will do so, as will 75 percent of commercial apps, and over 90 percent of consumers will engage with AI chatbots.
The sudden commercial incentive to help businesses and civic authorities make sense of this new explosion of data will see the emergence of innovative new models, to make AI and analytics services faster to deploy, more affordable, and ready to support DevOps models. Again, collaboration will be key to making the most of this new reality for all concerned – open source approaches will lower barriers to entry for companies hoping to contribute to innovation on AI. End-users will in time also play a more active role in this process – where mobile operators have until now been using AI and analytics largely for their own processes, many are now preparing to offer these as a service to customers. Developments of this kind will only be possible if we can make good on the ‘intelligence’ part of the AI equation in this new landscape of abundant big data, and innovators are well on the way to ensuring that we can.
