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Core Technologies Powering the IIoT Machine

Understanding Three Technologies That Are Helping Industries Leverage the Industrial Internet of Things. This Technological Trident Is Predicted to Be the Future of Capital-Intensive Industries.

Globally, the Industrial Internet of Things (IIoT) is building a robust bridge between Information Technology (IT) and Operational Technology (OT). The confluence of IT and OT opens a multitude of avenues for capital-intensive industrial sectors. Especially, industries related to Manufacturing, Healthcare, Oil & Gas, Utilities & Aviation will reap benefits, thanks to IIoT capabilities.

In a report, the General Electric Company, that coined the term IIoT, quoted the following statistics:

  • The IIoT can benefit 46% of the globe’s economy
  • The potential of IIoT to impact energy production remains at 100%
  • As for energy consumption, the global impact is pitched at 44%
  • 2020 will see IIoT becoming a $225-billion market

So, how are enterprises defining IIoT?

What is IIoT?

Mitch Lee
Mitch Lee

Mitch Lee, Profit Evangelist, Vendavo, spoke to us exclusively for insights on IIoT.

“IIoT is a special case of IoT, and often conflated with AI for autonomous control of industrial processes and machines.”

“For those involved in the process/chemical industries, Internet of Things sounds more than a little familiar. IoT is effectively enabling devices — usually with some type of sensor or measurement aspect — to be linked so that the information is available for other systems for consideration, and even calculation of control aspects.”

“In the 1960s, chemical and process industries started controlling their most complex plants by using various types of Distributed Control Systems (DCS).  In a DCS, signals from sensors throughout the plant — used to measure temperature, flow, speed, levels, etc. — were tied to central computers that leveraged those measurements to control valves, motors, heat sources, etc. In this way, real-time information from the world was brought into the control mechanism for — you guessed it — consideration and even calculation of control aspects.  Not exactly AI, but it is certainly more consistent and reliable than a person being in control.”

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“So, yes, a DCS is a closed system. Think: A Local Area Network set up with firewalls by design, for security control and the IIoT is “open” for anything that has access to the internet and yes, with security measures to appropriately reduce risk.  But as you can see, today, that distinction seems relatively small — your car probably sent you an email this month to let you know that it has a service appointment — compared to the basic idea of using information from the field to guide central control.  Perhaps the openness of the IoT is the most significant aspect. Yes, of course, you have lots of “internal” data coming to your control system, but now, you can consider adding external data sources to augment the data pool you are using for decision context, regardless of whether it’s a system or a person that’s doing the controlling.”

IIoT is a largely magnified version of IoT.

IoT is predominantly used in products that consumers use on a daily basis. Hence, IoT capabilities are used in autonomous cars, consumer electronics, residential complexes, etc.

IIoT, on the other hand, is exclusively used in industries that cannot operate without costly machinery. IIoT is being used in oil rigs, core manufacturing, energy industries, etc.

So, IoT can tell a homeowner that the milk in the refrigerator is about to get spoilt. IIoT though, will tell industry stakeholders that a particular wind turbine in a windmill will fail in three days.

A gallon of milk costs a maximum of 4 dollars. The cost of a wind turbine, however, can go up to $2.2 million. In this case, by leveraging IIoT capabilities windmill energy farm stakeholders just saved a lot of money.

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The real power behind IIoT

The sphere of IIoT consists of three core technologies. Here is a brief description of each one of them:

Edge Computing

IIoT has enabled business networks with several endpoints. Nowadays, IIoT allows recording of data from several sources. These sources can be far away from the main data center or a network’s core processing unit. Hence, making this data reach the data center for further processing becomes a challenge.

This is where Edge Computing comes into the picture. This technology is equipped with a minor amount of storage, which allows it to work closer to the source of the data. This valuable data can be later sent forward for accurate processing.

Edge Computing is the current stage of evolution from its predecessors, some of which are:

  • Peer-to-peer networking
  • Distributed data
  • Self-healing network technology
  • Remote cloud services

Think of an Edge Computing Device as a miniature replica that consists of a home computer’s attributes. The device runs on low power and is equipped with an array of Flash Storage to store data coming from a source. The quality of processors is such that it enhances hardware security and delivers, surprisingly, optimized performance.

Enterprises that make these devices possible ensure compatibility with data transporting gateways in the IIoT architecture. Hence, the short of it is that Edge Computing works with embedded computing components that directly interface with sensors, controllers, etc.

Standout points that are making Edge Computing popular are:

  • Edge Computing works in areas of extremely low latency. Hence, demographic locations where there is low internet availability can harness the power of Edge Computing. Examples are oil rigs, mines, marine research. etc.
  • Since Edge Computing works at the data source, it does not interfere with data traffic towards the Data Center. This avoids a data traffic bottleneck entirely.
  • Edge Computing encrypts data closer to a commercial network’s core while ensuring that data away from the core is highly optimized.

Industrial networks need control of Edge Computing because it is based on a bi-directional system of data exchange. Data produced out of Edge Computing is usually transported to Fog Computing.

Yoni Kahana
Yoni Kahana

We spoke to Yoni Kahana, VP Customers of NanoLock Security, to understand how Edge Computing fits into the scheme of Industrial Internet of Things. He said, “The Industrial Internet of Things (IIoT) relies on data from many sensors, controllers and attached servers, often across multiple, remote locations. So, certain data processing tasks need low latency and are best performed ‘at source’ rather than in the cloud. Therefore, Edge Computing is a key component in the IIoT. In order to rely on this information, the data needs to be trustworthy and for this, the end device should be trusted. Moreover, when there is a large number of end devices, it is required to manage it in an efficient manner and get notified if the end device is malfunctioning. “

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Fog Computing

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Morris Novello, Senior Director of Marketing, Nebbiolo Technologies
Morris Novello

Speaking to us about Fog Computing, Morris Novello, Senior Director of Marketing, Nebbiolo Technologies, said, “Fog Computing, the ‘Fog,’ is a complement to Cloud Computing. It is the Cloud moving down, “closer to the ground,” to the end systems, the machines, the sensors, and actuators.

The Fog is secure, highly available, virtualized, real-time capable edge computing, networking, and storage, which will enable a powerful convergence between Information Technologies and Industrial Operational Technologies.

We are proudly part of the OpenFog Consortium.

Fog Computing is the platform that brings modern, cloud-inspired computing, storage, and networking functions closer to the data-producing sources, while also integrating real-time and safety capabilities.

Fog Computing provides a unified solution at the edge for communications, device management, data harvesting, analysis, and control. Fog Computing enables the deployment of a highly distributed but centrally managed infrastructure.

Fog Computing is applicable across all IoT industry verticals.”

Nebbiolo’s has worked extensively to implement Fog capabilities in various sectors.

As a concept, Fog Computing is similar to Edge Computing. Fog Computing too, works close to the source of data. However, the biggest difference between Fog Computing and Edge Computing is how they process data and derive intelligence out of it.

Edge Computing processes data on a very local level. But, Fog Computing entrusts a Local Area Network to do all its computing. Hence, the short of it is that Fog Computing is the gatekeeper between two extreme endpoints in a commercial network. While one endpoint is data coming from the source, the other is the network’s core for this data to be super processed.

Fog Computing also further transmits data coming from the network’s core to the source for Edge Computing to evolve. Hence, Fog Computing is the exact middle of a bi-directional data exchanging business channel.

Core hardware components of Fog Computing are the actual Edge Devices and the LAN networks that power data transmission gateways. Since Fog Computing is a near continuous process, its hardware infrastructure needs to be efficient. Hardware also needs to consume less power and emit very less heat.

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Cloud Computing

Most enterprises globally are well versed with Cloud Computing. A Cloud Server nullifies an enterprise’s need to install an in-house IT infrastructure for storing and processing of organizational data. This discovery has allowed companies to save on overheads arising out of the purchase and maintenance of IT assets.

Fog and Edge Computing are both off-springs of Cloud systems but on a very micro level. The biggest advantage of Cloud Computing is that it can store and process data coming from any part of the world. Hence, data from Fog and Edge systems can be processed in the Cloud computing infrastructure.

The way this works is hardware systems transmit IIoT data from the Edge layer to the Fog layer. This combined data is then sent to the Cloud layer, which is in most cases at a different geographical location. This is where the Cloud layer benefits from IIoT devices.

This vast amount of data is then processed, which allows stakeholders to obtain superior data-based insights. The derived insights are then transferred back to the Fog and Edge layers so that machines can be made to operate in the desired way.

Insights are directly sent to humans on-site who are responsible for industrial machinery handling.

The IIoT Model

Enterprises have the complete liberty to choose between these three technologies. Enterprises can integrate Cloud Computing with Edge or Fog Computing. This integration is even possible for both the layers, that of Fog and Edge. The current trend though is of enlarging Fog or Edge Computing resources. Enterprises are trying to increase efficiency on the end-user level, quickly.

Hence, depending on organizational needs, enterprises can stick to a Fog-Edge combination and process data there. The main goal is to reduce data traffic to and fro into business systems and to keep a check on machine quality. Better data insights allow more business control, help in predictive maintenance and increase overall business efficiency.

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Who Processes the Data?

Enterprises that facilitate Cloud Computing are enabling its users with powerful tools for business analysis. Leading this pack is Amazon, Microsoft, and Google, all three that have competing Cloud Infrastructure.

However, IIoT data is unique and as such software platforms utilized to process this data need to be customized. Companies that specialize in IIoT platforms are –

Key Takeaways for CIOs

IIoT is here to stay! IIoT is helping major corporations to optimize their machinery without replacing it. It is also enabling enterprises to save on maintenance costs and focus on other key areas of expanding businesses.

In a nutshell, technologies powering the IIoT machine should be seen as a relay race. Each technology is running a certain distance and asking the next technology to continue the race. This is if enterprises adopt the full IIoT model.

Businesses can absorb customizable models as well depending on business needs. IIoT is also shedding light on newer avenues of business. This is good news for original equipment manufacturers (OEMs) for autonomous control of their products.

Currently, OEMs are taking a huge hit on ROI because products that they manufacture are being leveraged by third parties. This means that third parties are developing spin-off products on machinery developed by an OEM.

With the presence of IIoT, they can directly link and re-invent their own products to cater to several other needs, in turn, increasing their ROI.

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