The Emergence of Application-Specific IoT

By September 14, 2014Internet of Things, M2M, Strategy

General IoT vs. Application-Specific IoT

2014 Gartner Hype Cycle Special Report

2014 Gartner Hype Cycle

Gartner recently published the 2014 Gartner Hype Cycle Special Report, which evaluates the market perception and penetration for over 2,000 technologies, services and technology trends. Of particular interest to many was the placement of the Internet of Things (IoT) at the top of the Peak of Inflated Expectations. Gartner defines the Peak of Inflated Expectations as: “Early publicity produces a number of success stories—often accompanied by scores of failures. Some companies take action; many do not.”

And, indeed, inflated market size forecast and grandiose visions of IoT reign supreme. Morgan Stanley forecasts that by that by 2020 there will be75 billion connected devices, whereas Harbor Research estimates the same market will consists of a meager 8 billion connected devices. Gartner estimates that by 2020 there will be 26 billion connected devices, IDC counters that with 30 billion connected devices, Cisco says 50 billion… you get the picture.

Do you think they really know? The typical rationale offered by industry analysts is that they use different market and technology taxonomies, hence the vast differences.

On the other hand, does it really matter that much?

What matters is the data these devices can collect and the business value they provide when connected to each other and to advanced analytics and decision-support applications.

Gartner estimates a time span of 5-10 years from the Peak of Inflated Expectations to the Plateau of Productivity, or, simply put, technology and market maturity, i.e. the ability to achieve a sustainable business value. As I commented elsewhere, when it comes to the IoT Gartner may be somewhat optimistic about the time to maturity.

But it appears that many in the press as well as in industry do not subscribe to Gartner’s assessment and timeline. The IoT gets much attention these days, ranging from breathless headlines to long term strategy decisions by companies that span the gamut from onboard data acquisition and wireless communication hardware to enterprise software.

Regrettably, there are still as many trivial IOT scenarios as there are serious ones and, by and large, we are still awaiting the realization of the exponential growth in IoT revenues the pundits are promising. Even investors that too often pursue early technologies and unsubstantiated business ideas, sometimes inexplicably, are lukewarm about the potential value of the dozens of companies in the IoT space, most of whom are generating less than $10M in revenue.

There are certainly interesting and valuable business solutions based on device connectivity. Until recently we simply called them Machine to Machine (M2M) communication.

How will IoT fans, pundits and especially company CEOs betting their company business on IoT explain the disparity between the vision and the reality? We are already witnessing the introduction of new “classes” of IoT such as the “industrial IoT”. I expect that we will witness the emergence of “application-specific IoT” and “industry-specific IoT”, which, in so many ways, will not be that different from the many M2M technology implementations that address narrowly defined yet no less valuable business opportunities such as the solutions implemented, for example, by Axeda at Diebold, EMC, GE Healthcare, and Philips Healthcare.

What does the IOT need in order to make faster progress towards realizing the bold vision of “billions of connected devices”?

Conduit vs. Content

We often think of the evolution of the World Wide Web as a model that the IoT will follow. In fact, there is an assumption that with the proliferation of instrumented devices and pervasive commutation, the adoption rate of the IoT will be much faster than that of the Internet. However, the WWW model fostered a culture of collaboration and open standards such as hypertext, HTML and common page browsers; the W3C consortium develops and maintains standards and connects developers and users.

The IOT industry does not seem to converge in this direction; almost the opposite. The space is inundated by numerous of communication standards and data protocols that aren’t interoperable, and companies offering as many one-off solutions to attempt to connect devices using incompatible communications methods and interfaces.

What do we mean when we say “connected devices?” Connect to what? How? What for?

The business value proposed by the IoT does not end in enabling connectivity among devices. We are approaching the point where, thanks to the WWW, everything and everyone is a roaming IP node. Connectivity itself isn’t the point – it is in exploiting the information devices generate, collect and transmit.

The business potential is not in the conduit, or the “plumbing” of the IoT; it is in the content.

However, the data streams of disparate devices cannot be simply connected. Nor can the portfolio of dissimilar applications communicating with these devices be simply daisy-chained as depicted by those futuristic scenarios.

Data interoperability is critical to harvest the potential value of the IoT’s content and to enable new meaningful business models that utilize its data. That means not only compatible and interoperable data protocols, but also, more critically, data models and common semantics, so that disparate devices and services can be linked, aggregated and harmonized to form an IoT solution.

Security

Security is an obvious concern, especially when considering the plethora of consumer devices from obscure, untested and potentially rogue sources. These scenarios are all over the IOT-of-the-future space: cars hacked, manufacturing lines shut down, utilities brought down through malicious acts, and many others.

Related to this topic are questions related to data privacy and data use rights.

Although there isn’t an immediate response to these challenges, it’s logical to assume that it will be easier to implement and control both technical solutions and legislation if embodied in a small set of open standard IoT interoperability mechanisms.

In the meantime, security and privacy concerns will slow down the broad adoption of the “general IoT.”

Reaching a Critical Mass

Although connecting devices to the Internet is getting easier technologically, there are several additional factors to consider, such as the interoperability and security points I discussed above. But even if we focus on the industrial “application specific IoT” (M2M), in which those aspects are easier to manage, there are still forces at work that hinder the overnight explosion in connectivity some predict.

Many interesting IoT scenarios assume that facilities and assets such as factory equipment, cars, buildings, railroad tracks, highways and many other “things” become connected overnight. In reality, it will take many years for older assets to be replaced or retrofitted to support connectivity. A few examples will illustrate that point.

The average age of passenger and light duty-vehicles in the U.S. is 12.4 years and it continues to rise. Even if all new cars sold are Internet-of-Things-capable tomorrow, it will take several long years until there are enough connected cars on the road to reach the promised safety and traffic management benefits.  On the manufacturing side, the average age of industrial equipment in the U.S. has risen above 10 years—the highest since 1938. At the same time, the growth in capital spending by manufacturing companies is growing at a slow pace. Let’s look at energy. 50% of the U.S. power generating capacity is at least 30 years old.

Looking Ahead

The Internet of Things is not a new Internet. For there to be an Internet of Things, someone has to put the Internet in those things, and then those things have to be placed on the Internet and connected in a manner that realizes a meaningful and worthwhile business value. And, by definition, this value does not occur until there are many devices that connect and communicate effectively and securely.

Until we put the Internet into things—actually, until we put the business into things—there will be no real “Internet of Things”; just a lot of “things” that connect over the Internet, but not necessarily to each other: M2M all over again. (With attribution to Mike Elgan.)

Learn More

  • Joe – great article, thanks for posting. I agree with all that you stated and in particular – putting the right analytics framework in place to derive insights, drive action and achieve positive outcomes. Otherwise, as you said, it’s just a lot of “things” connected. Your readers might be interested this IoT page we put together to learn more about the important role of cyber-security and business analytics in the IoT.

  • Thanks Mike. Can you post the complete URL to the IOT page you are referring to?

  • Joe, great summary of challenges and strategies related to IoT.

    One thing to add – the challenge of data management and analytics related to IoT data. PLM databases will be blown up by amount of data

    http://beyondplm.com/2014/09/23/iot-data-will-blow-up-traditional-plm-databases/

    Just my thoughts…

    Best, Oleg

  • Pingback: The Emergence of Application-Specific IoT - Joe Barkai()