The Internet of Things will connect existing systems and then augment those by connecting more things, thanks to wireless sensor networks and other technologies. Things on the 'edge' form mesh networks and can make their own automated decisions. But where and how, in the scale of hype to reality, can the Internet of Things profit suppliers and users today? What are the pragmatic steps needed to enable the Internet of Things and widespread deployment of wireless sensor networks that are feasible and based on an ROI and not the hope someone else will pay for this? Who is buying IoT in the short term?
A look into some of the main IoT trends for 2017, based on research, observations and different sources.
In March 2017, market research firm Ovum released a list of essential IoT trends for 2017, in collaboration with Internet of Things World. That seemed like a good opportunity to cover some major key IoT trends and predictions too.
We tackle the 5 essential Internet of Things (IoT) trends worth watching in the overall Internet of Things market according to the the organizers of Internet of Things World 2017 and Ovum, add some context and comments and, while we were at it, add over a dozen IoT trends.
The growth of scalable IoT projects and rise of cross-industry IoT deployments
First things first: the 5 IoT trends as reported by the two mentioned parties. Ovum stresses that 2016 was an important year for the Internet of Things but that 2017 is even more important and disruptive, both for the IoT technology players and the many industries where IoT projects are being deployed.
In fact, here is already one IoT trend we can add: based on data regarding the increasing maturity, scalability and deployment of effective IoT projects, beyond the proof of concept stage, this move towards scalable IoT projects is an IoT trend for 2017 for sure. That was our IoT trend number 1.
M&A activity in the IoT market will increase as providers continue to differentiate their offerings
Today, the majority of ‘significant and disruptive’ IoT trends as Ovum puts it are still mainly happening in industrial settings such as manufacturing (Industry 4.0), transportation and utilities, certainly from an IoT spending perspective. Other IoT projects relate to automotive, retail, consumer IoT, ad hoc IoT-enabled smart city projects and so forth. Moreover, cross-industry IoT use cases and deployments are on the rise and will rise even more in 2017 which is IoT trend number 2. Update: according to June 2017 data by IDC on IoT investments, cross-industry IoT cases will reach $86 billion by the end of 2017. That is more than the second largest industry from an IoT investment perspective (transportation, good for $85 billion).
Taking all this into account and without further ado a look at those five key IoT trends for 2017, as reported by Ovum and Internet of Things World 2017.
IoT connectivity: LPWA technologies become mainstream
The first key IoT trend for 2017, according to Ovum (that’s IoT trend number 3 in our list so far) is the fact that LPWA(N) goes mainstream and is poised to support far more Internet of Things use cases.
The announcement doesn’t mention Low-Power Wide-Area Network (LPWAN) technologies in the unlicensed spectrum such as LoRa and Sigfox, to name just two. Ovum and Internet of Things World 2017 rather point out Narrowband IoT (NB-IoT) and LTE-M (Long Term Evolution for Machines). In other words: Ovum emphasizes the cellular LPWA evolutions or the two standards which have been standardized within the 3GPP (3rd Generation Partnership Project).
Among the main IoT use cases for LPWA which Ovum mentions: smart city applications, smart metering and the connected home.
Non-cellular LPWAN technologies such as LoRa and Sigfox are also used in many smart city projects and virtually all applications where a low-cost, low-bandwidth and long battery life technology is needed, precisely what LPWA, whether it’s cellular or not, is all about.
IoT connectivity: non-cellular LPWAN will prove to be underestimated
Although unlicensed LPWAN technologies today account for a relatively small portion of all IoT cases and investments, we’re pretty sure that, certainly in the increasing number of countries where nationwide coverage exists and in the many large cities and regions where they are planned, they will more than add to the fact that LPWA goes – more – mainstream, with an increasing number of IoT use cases and deployments as a result.
And that brings us to ‘our’ IoT trend number 4. If we look at the many projects where unlicensed spectrum LPWAN is being deployed (e.g. a LoRaWAN testbed in London), the advent of decent new actors in the field (e.g. TrackNet, which raised $7 million), the large companies which are investing in LPWAN players and ecosystems (take a look at the list of the investors in the latest Sigfox investment round) and the technological evolutions whereby multiple connectivity solutions get supported, among other reasons, we believe that the non-cellular LPWA market is underestimated and its growth is yet another IoT trend for 2017 as investments outside the Industrial Internet of Things will grow and companies will roll out low-risk pilots.
If you want an example of the – according to us, underestimated – role of non-cellular LPWA, take a look at what the Airport of Schiphol in The Netherlands is doing.
What is true though is that the non-cellular market evolved first and mainly outside of the US, according to us a reason why it’s underestimated (for now).
IoT security becomes a top IoT priority
This seems like an obvious prediction or, rather IoT trend (number 5), not just given the many security incidents in 2016. If IoT security would not become a core focus for enterprises and providers as Ovum and Internet of Things World put it, we would have a serious issue.
As mentioned previously, and as Ovum also states, security needs to be and will be part of every SERIOUS IoT deployment discussion. This is not just the case for consumer-oriented IoT but also for Industry 4.0 and the Industrial Internet of Things. As we tackled previously, security concerns remain a key showstopper in IIoT, where attacks are on the rise, as well.
64% of security professionals recognize the need to take precautions against IIoT attacks as they increase
Moreover, just security isn’t enough. While security concerns the protection of data and the related technologies, we also need to look at the protection of personal data, what privacy is all about. Blockchain (see below) is poised to play an increasing role here.
IoT regulation becomes a key priority
One of the reasons to do so is the regulatory context. Think about the GDPR and the ePrivacy Regulation, for instance.
In fact, Ovum states that IoT security is coming onto the radar for regulators, which for us is yet another IoT trend as such (that’s number 6 if we counted well). As we mentioned and as we suppose Ovum means, this is also the case outside the scope of EU regulations.
Time for IoT trend number 7. According to the announcement of Ovum, Big Data and machine learning will unlock new IoT opportunities.
With this key IoT trend, Ovum in fact summarizes several evolutions. One is the clear shift of the delivery of IoT data analytics to the point of data capture/aggregation or the edge. Indeed: the fog or fog computing. Once more, we believe that this too is an IoT trend for 2017 as such: the fast rise of fog computing (IoT trend number 8).
A second evolution in the context of Big Data, analytics and machine learning is the rise of new tools for streaming data analytics, Ovum states (IoT trend number 9). Both evolutions fit in a context of the enablement of leveraging IoT data to feed all sorts of artificial intelligenceapplications, including the feeding of machine-leaning engines.
The growth of as-a-service business models
IoT trend number 10 (five in the list of Ovum and Internet of Things World 2017): the disruptive impact of the IoT will drive the growth of new as-a-service business models.
Most definitely yes. In fact, if you look at a large majority of Industrial Internet of Things cases (look at the case of ABB Robotics, for example, there are plenty more) one of the key digital transformation effects on a business model level is the move towards information-based business models and as-a-service models, making quite some large players develop entirely new services and shifting business models.
We definitely also agree that these ‘innovative business models will continue to evolve in many IoT verticals’ as Ovum predicts, including as-a-service and event-based charging models.
The adoption of as-a-service IoT solutions
We’re adding IoT trend 11 for 2017 here: the growth of as-a-service-models IN the Internet of Things solutions and deployment ‘stack’.
Just as the Internet of Things continues to drive evolutions towards as-a-service model, companies with Internet of Things projects will increasingly use platforms and solutions to enable them in an as-a-service approach. Just one example: Internet of Things security as a service is poised to grow fast.
By 2021, overall market revenues for IoT managed security services are poised to surpass $11 Billion
IoT service providers will increasingly focus on a diversification regarding technologies
The reason: customer needs become more diverse. This is definitely another IoT trend (number 12).
As we see more complex and scalable IoT deployments this is an inevitable evolution. It happens on all levels. Although strictly not a service provider, Cisco for instance already supports several technologies for client projects. The same happens with service providers on other levels. According to Ovum, service providers will also focus more on developer outreach.
The growth and increasing diversity of an IoT channel
We’ve covered all the Ovum trends so let’s look at some more.
IoT trend number 13: an IoT channel will continue to emerge and grow as IT service firms, vendors and distributors seek to diversify revenues and offerings, adding IoT to their portfolios in the scope of their existing strengths in particular areas (e.g. verticals, security, etc.).
This will also happen outside or IT and telecom and among businesses that are not typically part of the IT channel. Examples include marketing firms, offering IoT solutions for which they’ll also need IoT technologies and facility management and smart building companies, convincing their existing channel partners to include IoT solutions in their offerings for existing and new end customers.
Ten more IoT trends and predictions for 2017
We have 13 IoT trends but let’s summarize some more and of course there are even more than those we mention next…
Although 5G is not ready for prime-time, we’ll see industry consortium efforts grow to push the 5G agenda and market. This will happen within the Fog Consortium Group’s efforts and in new industry initiatives.
The attention for blockchain and IoT convergence will grow, yet blockchain flaws will need to be fixed as public key is a no-brainer for quantum computers.
As growth, securtity, analytics and connectivity will require more AI and IBM is boosting its Watson IoT spend and initiatives the battle for AI IoT dominance will increase, mainly for specific verticals.
M&A activity in the IoT market will increase as providers continue to differentiate their offerings.
Consumer IoT adoption will grow but regulatory uncertainties in specific regions will surface new security and privacy challenges, among others regarding voice assistants.
Healthcare payers will step up their efforts to deploy new ways to connect IoT data with healthcare plans.
Disappointment regarding early smart city IoT deployments will grow while new smart city IoT deployments will increasingly fit in the holistic smart city picture and will be driven by real challenges.
Retailers will invest less in testing a variety of IoT use cases and focus more on the supply chain and use cases that offer immediate benefits.
The adoption of wearables will grow faster than expected outside of the consumer wearables context and in verticals such as healthcare and manufacturing.
IT and OT integration in the Industrial Internet is on the rise but hindred by security concerns, slowing down integration.
The number of connected devices will grow and there will be more security breaches.
Analysts Will Discuss Cloud Security at the Gartner Security & Risk Management Summits in London and Dubai
Rapid growth in cloud adoption is driving increased interest in securing data, applications and workloads that now exist in a cloud computing environment. The Gartner, Inc. Hype Cycle for Cloud Security helps security professionals understand which technologies are ready for mainstream use, and which are still years away from productive deployments for most organizations (see Figure 1.)
"Security continues to be the most commonly cited reason for avoiding the use of public cloud," said Jay Heiser, research vice president at Gartner. "Yet paradoxically, the organizations already using the public cloud consider security to be one of the primary benefits."
The attack resistance of the majority of cloud service providers has not proven to be a major weakness so far, but customers of these services may not know how to use them securely. "The Hype Cycle can help cybersecurity professionals identify the most important new mechanisms to help their organizations make controlled, compliant and economical use of the public cloud," added Mr. Heiser.
Figure 1. Hype Cycle for Cloud Security, 2017
Source: Gartner (September 2017)
At the PeakThe peak of inflated expectations is a phase of overenthusiasm and unrealistic projections, where the hype is not matched by successful deployments in mainstream use. This year the technologies at the peak include data loss protection for mobile devices, key management as-a-service and software-defined perimeter. Gartner expects all of these technologies will take at least five years to reach productive mainstream adoption.
In the Trough When a technology does not live up to the hype of the peak of inflated expectations, it becomes unfashionable and moves along the cycle to the trough of disillusionment. There are two technologies in this section that Gartner expects to achieve mainstream adoption in the next two years:
Disaster recovery as a service (DRaaS)is in the early stages of maturity, with around 20-50 percent market penetration. Early adopters are typically smaller organizations with fewer than 100 employees, which lacked a recovery data center, experienced IT staff and specialized skills needed to manage a DR program on their own.
Private cloud computing is used when organizations want to the benefits of public cloud — such as IT agility to drive business value and growth — but aren’t able to find cloud services that meet their needs in terms of regulatory requirements, functionality or intellectual property protection. The use of third-party specialists for building private clouds is growing rapidly because the cost and complexity of building a true private cloud can be high.
On the SlopeThe slope of enlightenment is where experimentation and hard work with new technologies are beginning to pay off in an increasingly diverse range of organizations. There are currently two technologies on the slope that Gartner expects to fully mature within the next two years:
Data loss protection (DLP)is perceived as an effective way to prevent accidental disclosure of regulated information and intellectual property. In practice, it has proved more useful in helping identify undocumented or broken business processes that lead to accidental data disclosures, and providing education on policies and procedures. Organizations with realistic expectations find this technology significantly reduces unintentional leakage of sensitive data. It is relatively easy, however, for a determined insider or motivated outsider to circumvent.
Infrastructure as a service (IaaS) container encryption is a way for organizations to protect their data held with cloud providers. It’s a similar approach to encrypting a hard drive on a laptop, but it is applied to the data from an entire process or application held in the cloud. This is likely to become an expected feature offered by a cloud provider and indeed Amazon already provides its own free offering, while Microsoft supports free BitLocker and DMcrypt tools for Linux.
Reached the PlateauFour technologies have reached the plateau of productivity, meaning the real-world benefits of the technology have been demonstrated and accepted. Tokenization, high-assurance hypervisors and application security as a service have all moved up to the plateau, joining identity-proofing services which was the only entrant remaining from last year’s plateau.
"Understanding the relative maturity and effectiveness of new cloud security technologies and services will help security professionals reorient their role toward business enablement," said Mr. Heiser. "This means helping an organization’s IT users to procure, access and manage cloud services for their own needs in a secure and efficient way."
Gartner clients can read full analysis on the technologies in this Hype Cycle in "Hype Cycle for Cloud Security, 2017." This research is part of the Gartner Trend Insight Report "2017 Hype Cycles Highlight Enterprise and Ecosystem Digital Disruptions." With over 1,800 profiles of technologies, services and disciplines spanning over 100 Hype Cycles focused on a diversity of regions, industries and roles, this Trend Insight Report is designed to help CIOs and IT leaders respond to the opportunities and threats affecting their businesses, take the lead in technology-enabled business innovations and help their organizations define an effective digital business strategy.
Gartner analysts will provide additional analysis on IT security trends at the Gartner Security & Risk Management Summits 2017 taking place in London; and Dubai. Follow news and updates from the events on Twitter at #GartnerSEC.
Artificial intelligence, machine learning, and smart things promise an intelligent future.
Today, a digital stethoscope has the ability to record and store heartbeat and respiratory sounds. Tomorrow, the stethoscope could function as an “intelligent thing” by collecting a massive amount of such data, relating the data to diagnostic and treatment information, and building an artificial intelligence (AI)-powered doctor assistance app to provide the physician with diagnostic support in real-time. AI and machine learning increasingly will be embedded into everyday things such as appliances, speakers and hospital equipment. This phenomenon is closely aligned with the emergence of conversational systems, the expansion of the IoT into a digital mesh and the trend toward digital twins.
Three themes — intelligent, digital, and mesh — form the basis for the Top 10 strategic technology trends for 2017, announced by David Cearley, vice president and Gartner Fellow, at Gartner Symposium/ITxpo 2016 in Orlando, Florida. These technologies are just beginning to break out of an emerging state and stand to have substantial disruptive potential across industries.
Intelligent
AI and machine learning have reached a critical tipping point and will increasingly augment and extend virtually every technology enabled service, thing or application. Creating intelligent systems that learn, adapt and potentially act autonomously rather than simply execute predefined instructions is primary battleground for technology vendors through at least 2020.
Trend No. 1: AI & Advanced Machine Learning
AI and machine learning (ML), which include technologies such as deep learning, neural networks and natural-language processing, can also encompass more advanced systems that understand, learn, predict, adapt and potentially operate autonomously. Systems can learn and change future behavior, leading to the creation of more intelligent devices and programs. The combination of extensive parallel processing power, advanced algorithms and massive data sets to feed the algorithms has unleashed this new era.
In banking, you could use AI and machine-learning techniques to model current real-time transactions, as well as predictive models of transactions based on their likelihood of being fraudulent. Organizations seeking to drive digital innovation with this trend should evaluate a number of business scenarios in which AI and machine learning could drive clear and specific business value and consider experimenting with one or two high-impact scenarios..
Trend No. 2: Intelligent Apps
Intelligent apps, which include technologies like virtual personal assistants (VPAs), have the potential to transform the workplace by making everyday tasks easier (prioritizing emails) and its users more effective (highlighting important content and interactions). However, intelligent apps are not limited to new digital assistants – every existing software category from security tooling to enterprise applications such as marketing or ERP will be infused with AI enabled capabilities. Using AI, technology providers will focus on three areas — advanced analytics, AI-powered and increasingly autonomous business processes and AI-powered immersive, conversational and continuous interfaces. By 2018, Gartner expects most of the world’s largest 200 companies to exploit intelligent apps and utilize the full toolkit of big data and analytics tools to refine their offers and improve customer experience.
Trend No. 3: Intelligent Things
New intelligent things generally fall into three categories: robots, drones and autonomous vehicles. Each of these areas will evolve to impact a larger segment of the market and support a new phase of digital business but these represent only one facet of intelligent things. Existing things including IoT devices will become intelligent things delivering the power of AI enabled systems everywhere including the home, office, factory floor, and medical facility.
As intelligent things evolve and become more popular, they will shift from a stand-alone to a collaborative model in which intelligent things communicate with one another and act in concert to accomplish tasks. However, nontechnical issues such as liability and privacy, along with the complexity of creating highly specialized assistants, will slow embedded intelligence in some scenarios.
Digital
The lines between the digital and physical world continue to blur creating new opportunities for digital businesses. Look for the digital world to be an increasingly detailed reflection of the physical world and the digital world to appear as part of the physical world creating fertile ground for new business models and digitally enabled ecosystems.
Trend No. 4: Virtual & Augmented Reality
Virtual reality (VR) and augmented reality (AR) transform the way individuals interact with each other and with software systems creating an immersive environment. For example, VR can be used for training scenarios and remote experiences. AR, which enables a blending of the real and virtual worlds, means businesses can overlay graphics onto real-world objects, such as hidden wires on the image of a wall. Immersive experiences with AR and VR are reaching tipping points in terms of price and capability but will not replace other interface models. Over time AR and VR expand beyond visual immersion to include all human senses. Enterprises should look for targeted applications of VR and AR through 2020.
Trend No. 5: Digital Twin
Within three to five years, billions of things will be represented by digital twins, a dynamic software model of a physical thing or system. Using physics data on how the components of a thing operate and respond to the environment as well as data provided by sensors in the physical world, a digital twin can be used to analyze and simulate real world conditions, responds to changes, improve operations and add value. Digital twins function as proxies for the combination of skilled individuals (e.g., technicians) and traditional monitoring devices and controls (e.g., pressure gauges). Their proliferation will require a cultural change, as those who understand the maintenance of real-world things collaborate with data scientists and IT professionals. Digital twins of physical assets combined with digital representations of facilities and environments as well as people, businesses and processes will enable an increasingly detailed digital representation of the real world for simulation, analysis and control.
Trend No. 6: Blockchain
Blockchain is a type of distributed ledger in which value exchange transactions (in bitcoin or other token) are sequentially grouped into blocks. Blockchain and distributed-ledger concepts are gaining traction because they hold the promise of transforming industry operating models in industries such as music distribution, identify verification and title registry. They promise a model to add trust to untrusted environments and reduce business friction by providing transparent access to the information in the chain. While there is a great deal of interest the majority of blockchain initiatives are in alpha or beta phases and significant technology challenges exist.
Mesh
The mesh refers to the dynamic connection of people, processes, things and services supporting intelligent digital ecosystems. As the mesh evolves, the user experience fundamentally changes and the supporting technology and security architectures and platforms must change as well.
Trend No. 7: Conversational Systems
Conversational systems can range from simple informal, bidirectional text or voice conversations such as an answer to “What time is it?” to more complex interactions such as collecting oral testimony from crime witnesses to generate a sketch of a suspect. Conversational systems shift from a model where people adapt to computers to one where the computer “hears” and adapts to a person’s desired outcome. Conversational systems do not use text/voice as the exclusive interface but enable people and machines to use multiple modalities (e.g., sight, sound, tactile, etc.) to communicate across the digital device mesh (e.g., sensors, appliances, IoT systems).
Trend No. 8: Mesh App and Service Architecture
The intelligent digital mesh will require changes to the architecture, technology and tools used to develop solutions. The mesh app and service architecture (MASA) is a multichannel solution architecture that leverages cloud and serverless computing, containers and microservices as well as APIs and events to deliver modular, flexible and dynamic solutions. Solutions ultimately support multiple users in multiple roles using multiple devices and communicating over multiple networks. However, MASA is a long term architectural shift that requires significant changes to development tooling and best practices.
Trend No. 9: Digital Technology Platforms
Digital technology platforms are the building blocks for a digital business and are necessary to break into digital. Every organization will have some mix of five digital technology platforms: Information systems, customer experience, analytics and intelligence, the Internet of Things and business ecosystems. In particular new platforms and services for IoT, AI and conversational systems will be a key focus through 2020. Companies should identify how industry platforms will evolve and plan ways to evolve their platforms to meet the challenges of digital business.
Trend No. 10: Adaptive Security Architecture
The evolution of the intelligent digital mesh and digital technology platforms and application architectures means that security has to become fluid and adaptive. Security in the IoT environment is particularly challenging. Security teams need to work with application, solution and enterprise architects to consider security early in the design of applications or IoT solutions. Multilayered security and use of user and entity behavior analytics will become a requirement for virtually every enterprise.
David Cearley is vice president and Gartner Fellow in Gartner Research and is a leading authority on information technology. Mr. Cearley analyzes emerging and strategic business and technology trends and explores how these trends shape the way individuals and companies derive value from technology.
