Navigant Research Blog

Harnessing IIoT Requires Collective Thinking

— July 12, 2018

One of the big challenges managers face when planning Industrial IoT (IIoT) projects is choosing the right architecture or approach for solving business problems. Managers don’t simply decide to buy some IoT technology one day and then install it. Instead, they look at an issue, such as how to reduce energy on a production line or how to lower maintenance costs on wind turbines, and then apply IoT technologies. And that is the problem: too many IoT options but too few case studies that provide best practices. This situation is starting to change, however. A couple of examples follow.

IIC Technical Guidance

First, the Industrial Internet Consortium (IIC) has produced a new white paper that offers practical guidance for deploying IIoT solutions within the concept of edge computing—a hot topic in the industry. The 19-page white paper defines edge computing architectural functions and underscores some key use case factors. The IIC white paper is aimed at technical people who have to implement IoT solutions, but this is the sort of document and shared learning necessary to drive wider adoption.

I spoke recently with two of the authors of the white paper, Mitch Tseng of Huawei and Todd Edmunds of Cisco, who pointed out that defining where the computing takes place in IIoT is less important than harnessing the technology in the right way to achieve valuable business outcomes. They also noted that both edge and cloud computing are important to many IIoT use cases, and the key is in orchestrating the various resources to optimize the outcomes.

Their work is not finished, by any means. The next step calls for the IIC to produce a more technical report that addresses in greater detail how to implement an IIoT architecture that is managed, orchestrated, trustworthy, and secure. Engineers who need to deploy IIoT solutions should benefit greatly from the collective thinking in that yet-to-be-published document.

Exploring Thing Query Language

Mark Venables recently noted the complexity in IIoT and the challenge to provide new tools in his online piece about Thing Query Language (TQL). He highlights Atomiton, a company founded 5 years ago that developed TQL as an operating system for enabling machines, equipment, or devices to talk to each other and that can be programmed, similar to Microsoft’s Visual Basic Programming language. The software is currently used in oil & gas, smart cities, agriculture, and industrial automation settings, but could be applied in other sectors as well. Atomiton was founded by Jane Ren, one of the original founders of GE’s digital arm.

Atomiton is not the only technology vendor working to smooth the pathway for IIoT implementations, of course. Other examples of companies providing valuable IIoT products or solutions include PTC, OSIsoft, Siemens, AWS, Microsoft, Oracle, and C3 IoT.

Collaboration in Using IIoT Solutions Shows Promise

Solving industrial problems with IIoT solutions is still in its early phase. No one company has the full stack of products or services to meet the corporate demand. A group of vendors working together or through an integrator has proven successful. As the Navigant Research Leaderboard: IoT Platform Vendors report noted, there are hundreds of firms offering solutions, which makes for a complex and sometimes confusing ecosystem. So, when efforts to simplify or provide valuable or tested approaches in using IIoT technology become widely known, it helps drive adoption and reduce wasted efforts. I’m all for that.

 

Automotive Sector and Smart Cities Join IoT and 5G Surge

— June 26, 2018

In a recent blog, I noted the gathering momentum for industrial IoT (IIoT) solutions. A similar IoT solution and connectivity trend is emerging in the automotive sector, among smart cities, in the buzzy 5G telecom world, and even in military circles. Of course, 5G is expected to play a role in the utility sector, too (see Navigant Research’s 5G and the Internet of Energy report). For stakeholders, 5G and IoT are worth paying attention; underneath the hype, important connectivity solutions are evolving and important strategic decisions are at stake.

Which Technologies Are Connecting Cars?

Among automakers, competing technologies vie for dominance in how connected cars will communicate with other vehicles and supporting systems. Much of the focus has been on 5G, which Ford, BMW, and other automakers support. Toyota favors dedicated short-range communications (DSRC), which is Wi-Fi-based. GM supports DSRC as well, and the US government has invested millions of dollars in the technology.

From a US perspective, 5G appears to have the upper hand in connected cars, especially as wireless carriers invest in upgrades to existing 4G systems. However, in other countries the picture looks slightly different. Volkswagen is supporting 5G for its Audi brand in the US and China, but in Europe the company is hedging its bets and will deploy a version of DSRC on VW-branded cars in Europe beginning next year. So, the technology choice remains unsettled, as noted by the numerous pilots or deployments in a blog by OnBoard Security’s Gene Carter. (For details about automotive communications, see Navigant Research’s Connected Vehicles report).

What about Smart Cities?

Among cities, 5G is gaining ground, too (see Smart City Communication Networks Market Overview for details). Sacramento, for instance, is all in for 5G and is on track to become a model for other cities to follow with projects that take advantage of 5G’s super high speeds, high capacity, and low latency. In Spain, the situation is similar to Sacramento. Wireless carrier Telefónica is deploying 5G in two cities that will become living laboratories. Over the next 3 years, 5G will be tested in automated driving scenarios in Segovia and Talavera de la Reina. The carrier expects to gain new insights from its 5G trials in these two cities, and later will deploy valuable features across its nationwide network.

The Military Is Also Interested in IoT

The military sector also has eyes on 5G and IoT. The US Air Force Academy, for instance, has a new 5-year R&D deal with AT&T that calls for joint work on IoT, cybersecurity, 5G, Smart Base solutions, software-defined networking, and other emerging technologies. The effort is part of the Air Force’s CyberWorx design center, a public-private endeavor to solve operational problems.

Don’t Forget the Telecoms

Likewise, there is new confidence from telecom equipment giant Ericsson related to IoT. The company has nearly doubled its forecast for the number of IoT connections in the coming years. Ericsson expects 3.5 billion IoT cellular connections by 2023, which is up from its November 2017 forecast of 1.8 billion. The change is due to faster-than-expected market growth in recent months. The company says both IoT and 5G promise new capabilities and use cases that will affect not only consumers, but many industries, such as utilities, automotive, and manufacturing, that are undergoing digital transformations.

Yes, 5G and IoT technologies still carry hype baggage. But trials, testing, and deployments are moving ahead. And the markets will unfold quicker than many people imagine.

 

Industrial IoT Gets Needed Technology Boost from Vendors

— June 14, 2018

For many businesses, the industrial Internet of Things (IIoT) has yet to take hold. Most are well aware of the concept, but have little practical experience with the intricacies of IoT deployments, or else lack a strategy for taking advantage of IoT. Lately, though, new tools and better approaches have become available to help move firms still on the sidelines to the playing field.

OSIsoft Cornering Collaboration

For example, OSIsoft has developed several ways of collaborating so clients can get the most from their operational data. The company is working with Amazon Web Services to simplify the analytics process that kicks in when a firm uses OSIsoft’s PI System. Also, the company has a new deal with Nokia whereby the two firms will jointly develop new business models based on integrating IoT with private LTE networks. The aim is to help customers more easily deploy predictive maintenance and communication infrastructure. Lastly, in the utility sector, OSIsoft is helping Japan’s Kansai Electric Power Company (KEPCO) use the PI System in a newer way, providing remote monitoring and real-time alerts to reduce grid downtime.

Sprint Looks to Capture the Small and Medium Business Market

US wireless carrier Sprint is another firm supplying a new IoT tool, in this case aimed not only at larger firms but also the often overlooked small and medium business market. Sprint has created its IoT Factory, an online marketplace offering pre-packaged IoT solutions. The marketplace is a collaborative effort that includes strategic partners myDevices, a creator of drag-and-drop IoT devices, and the Goldie Group, a firm that provides lifecycle services in the electronics and wireless industries.

Let’s Talk about Progress

Progress, a provider of application development and deployment technologies, has come out with a new self-service anomaly detection and prediction tool for the IIoT market. The firm’s DataRPM is said to be a first-of-its-kind offering that enables R&D and innovation groups to enhance their decision-making capabilities during IIoT proof-of-concept or piloting projects. The new tool is hosted on AWS, which is offering free trials of Progress’ DataRPM to qualified manufacturers.

And Then There’s Microsoft

Finally, Microsoft is forging ahead with efforts to promote its Azure IoT Edge capabilities. At its annual Build conference, the software giant announced that it is open-sourcing Azure IoT Edge Runtime, launching Project Kinect for Azure, and further embracing Kubernetes. What this means is Microsoft is all in on IoT. This was underscored by the announcement earlier in the year that it is tripling its previous spending on IoT.

Small Steps Add Up

Individually, these might appear to be mere small steps in the evolution of the IIoT market. Taken together, however, these efforts illustrate the type of technology development momentum necessary to drive adoption. These strategic moves should help reduce the complexities involved in IoT projects.

This is just the type of market development anticipated in Navigant Research’s most recent report on the subject, Industrial Internet of Things. The report notes how, unlike consumer markets for IoT, the industrial or enterprise adoption pace will be more measured in the near term, with a surge coming later. That pace is likely given how many companies take a more restrained approach to new technology. Established companies will be hesitant to fully adopt until the evidence shows that they will get the necessary ROI.

 

Making the Case for an Intelligent Edge in an IoT World

— June 12, 2018

Cloud computing gets plenty of attention in IT circles and among grid managers—it is hard to ignore when technology giants like Amazon, Microsoft, IBM, and others keep promoting their cloud solutions. But as the Internet of Things (IoT) concept gains momentum, new attention is being focused on intelligent edge and distributed computing.

This theme was prevalent at the recent Internet of Things World conference in Silicon Valley, where participants pointed out advantages that edge has over the cloud. Jesse DeMesa, a strategy partner at the venture capital firm Momenta Partners, said that a cloud-first or data center-first approach to IoT analytics will not work, and companies will ultimately move toward more autonomous systems. Many current IoT adopters, he said, focus on connecting, collecting, and storing data, while the “real value of data has a shelf life often measured in seconds.”

Getting the Edge on Costs

His point is well-taken. Looking back and analyzing large datasets for actionable insights via a cloud scenario does have value. But gleaning insights within seconds, or fractions of a second, at the edge and making immediate adjustments can be equally valuable, if not more so, when critical operations are at stake or the safety of nearby personnel is in play.

The need to rethink a cloud-first approach was emphasized for cost reasons by HarperDB CEO Stephen Goldberg. During a panel session, Goldberg said the bandwidth needed to push data to the cloud and the edge storage infrastructure is expensive, and ends up grabbing a significant share of the cost in an IoT deployment. He argued that a more distributed computing infrastructure, where edge devices already in place are doing as much computing as possible, is a more rational approach. This is true.

IoT vendors recognize this need for advanced intelligence at the edge. Recent examples of companies with new edge offerings include: SWIM EDX, which processes edge streaming data in real time; C3 IoT and Intel partnering on a new artificial intelligence (AI) appliance for optimizing applications that do not require cloud computing; and Edgeworx, a startup that builds software for edge gateways and micro data centers.

Edge Networks Get Sharper

The big tech players have noticed the growing edge computing need and the advantages of putting more and strategically useful computing horsepower there as well. Dell and Microsoft, for instance, have teamed up to create an integrated IoT edge platform. Amazon Web Services has updated its edge computing platform, called Greengrass, to incorporate machine learning capabilities. Similarly, Hewlett Packard Enterprise’s Aruba subsidiary launched a new network edge solution called NetInsight in March that uses AI to autonomously monitor corporate networks and optimize performance.

What this all means is that the edge of networks is getting smarter. It means companies deploying IoT solutions need a strategy that integrates edge, on-premise, or cloud computing architectures to take advantage of each for an enterprise’s or a grid operator’s own needs and applications. In some scenarios, a cloud architecture makes sense, or an on-premise solution. But more likely the complexity in these deployments will require a sophisticated blend of technologies. As my colleagues Richelle Elberg and Mackinnon Lawrence note in their Navigant Research white paper From Smart Grid to Neural Grid, the future mature Energy Cloud will be based on technologies that integrate ubiquitous connectivity, cloud-based AI, and edge computing. That same type of integration of computing power will be needed for enterprises beyond the energy grid that seek to harness IoT as well.

 

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