Who Wins In The Industrial Internet Of Things (IIoT)?

By Patrick Moorhead - October 29, 2013

When many non-techies hear the phrase, “Internet of Things” (IoT), their eyes glaze over and they get that sleepy or puzzled look. To those in the tech industry, it is looked at in two ways- to some it’s massive hype, but to others, a massive economic opportunity. I believe IoT is a huge business opportunity, and the only question is “what” and “when”.

I’ve segmented the IoT “what” into two main areas, the Human IoT (HIoT) and the Industrial IoT (IIoT) in a paper we introduced last week. While many of us are familiar with the Nike FuelBand, FitBits, Nest, and Revolv in the HIoT, there’s as much going on in connecting commercial HVAC and fleet systems in the world of IIoT. Companies like DIGI International, Echelon, and Freescale Semiconductor are going after this space in a big way. Yesterday, I published a deep-dive paper on the IIoT, but I’ll give you the abridged version below. The primary difference between IIoT and HIoT over the next few years is that the IIoT will incorporate over a century of existing, “brownfield” infrastructure like commercial boilers and fleet tracking while HIoT is an emerging set of “greenfield” services and technologies that must build infrastructure as it grows.  Designing for IIoT requires deep understanding of solution spaces and an ability to connect systems manufactured many decades apart. IIoT favors solutions vendors such as DIGI, Echelon, and Freescale, who have solid roots in the industrial control world. HIoT favors fast moving prototyping driven by leaps of faith in user experience (UX) and device design like Nest, FitBit and Revolv. The concept of “good enough” does not apply in the industrial world.  As mentioned in our previous IoT segmentation paper, IIoT end-points must be more robust than HIoT end-points. Sensors embedded in end-points are not much help if the data they generate can’t be collected and transmitted for analysis. I call these collection points “gateways.” There are many vectors along which we can measure end-point “robustness.” The table below summarizes these vectors: 


Industrial IoT (IIoT)

Human IoT (HIoT)

Market Opportunity



Product Lifecycle

Until dead or obsolete

Whims of style and/or budget

Solution Integration

Heterogeneous APIs

Vertically integrated



Identity & privacy

Human Interaction




0.9999 to 0.99999 (4–5 ‘9’s)

0.99 to 0.999 (2–3 ‘9’s)

Access to Internet

Intermittent to independent

Persistent to interrupted

Response to Failure

Resilient, fail-in-place

Retry, replace

Network Topology

Federations of peer-to-peer

Constellations of peripherals

Physical Connectivity

Legacy & purpose-built

Evolving broadband & wireless

Example Gateways

Commercial monitoring

Echelon SmartServer

Consumer home automation Revolv Hub

  • Market Opportunity: IIoT uses brownfield to describe the opportunity to connect more than a century of in-service mechanical and electrical systems to the Internet and therefore to new cloud-based services and analytics back-ends. Think 100 year-old boilers and HVAC systems in high-rises.
  • Product Lifecycle: IIoT products have long product cycles, and the products often must operate under extreme conditions, such as next to boilers, in automotive and jet engines, immersed in corrosive liquids, located in deserts, rain forests, volcanos, high altitude, and other hostile geographic environments
  • Solution Integration: Systems of systems installed and upgraded over decades of use, such as old HVAC boilers must be interoperable over at least one of many levels: physical, electrical, ABI, API, and network protocol interfaces.
  • Security: Industrial systems like HVAC and power controls must be secure to prevent unauthorized access and abuse of physical infrastructure.  Abuse of even as simple a feature as temperature control can have far-reaching real world impact.
  • Human Interaction: IIoT systems are rules-based. Therefore IIoT data flow is asymmetric and predominantly upstream, from sensor to gateway to cloud service, with only minor control feedback flowing back downstream.
  • Availability: We measure availability by counting “nines” and looking at the remaining unavailable time at each level of availability. Four to five nines is usually referred to as “high availability” (HA) and is what you would expect in the IIoT world.
  • Access to Internet: IIoT systems cannot assume continuous Internet access to the cloud. Network interfaces fail, the network itself may fail occasionally, external interference may temporarily overwhelm a communications channel with noise and effectively sever the connection, etc.
  • Response to Failures: Industrial systems must be resilient to failure because failure of components and subsystems is expected. These systems are designed to fail gracefully and in deterministic ways – some to save lives and health, like power generation and medical instrumentation, others to save money, resources, and time, like airline scheduling systems, so that they may be restarted quickly when repaired.
  • Network Topology: IIoT end-point devices are often designed to federate into wider communities, in order to leverage resources and accomplish larger-scale goals.
  • Physical Connectivity: Gateways should be agnostic to local physical network.  IIoT uses whatever physical network fits the best: twisted pair, power line, Ethernet, wireless, cellular, satellite, etc.
The Industrial Internet of Things (IIoT) favors component and solutions vendors Like DIGI, Echelon, and Freescale from the industrial control world who have extensive experience with a variety of legacy industrial connectivity solutions. These vendors specialize in understanding specific industrial usage models, and then they create domain expertise to translate those usage models into sensors, actuators, control logic, data aggregation, local network connectivity, and services layers. They have built experience in working with legacy industrial equipment built over the last century and developed trust from decades of working with customers. I have published a deep-dive paper on the IIoT here.
+ posts
Patrick founded the firm based on his real-world world technology experiences with the understanding of what he wasn’t getting from analysts and consultants. Ten years later, Patrick is ranked #1 among technology industry analysts in terms of “power” (ARInsights)  in “press citations” (Apollo Research). Moorhead is a contributor at Forbes and frequently appears on CNBC. He is a broad-based analyst covering a wide variety of topics including the cloud, enterprise SaaS, collaboration, client computing, and semiconductors. He has 30 years of experience including 15 years of executive experience at high tech companies (NCR, AT&T, Compaq, now HP, and AMD) leading strategy, product management, product marketing, and corporate marketing, including three industry board appointments.