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The Industrial Internet of Things (IIoT): Are Companies Ready For It?

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The Industrial Internet of Things (IIoT): Are Companies Ready For It?

Are Companies Ready For the Industrial Internet of Things?

We’ve all heard about how the consumer version of the internet of things (IoT) will impact our lives. Smart devices in our homes, cars, and cities are already beginning to send and receive data to each other, allowing for unprecedented integration with consumer technologies.

But the implications of this revolution of connectivity extend way behind just smartphones and your home. In fact, it’s about to be applied on an industrial scale to everything from aerospace to mining in ways that people can hardly imagine.

The Industrial Internet of Things (IIoT) will pull data from millions of tiny sensors on every piece of industrial equipment fathomable. Companies will harness this data in real-time to create insights and efficiencies on a crazy scale: GE estimates it will help to generate a $10-$15 trillion increase in global GDP over the next 20 years.

But can companies handle the IIoT?

While this all sounds great in theory, the reality is that the transition to a useful IIoT is going to be an ongoing challenge. Very different types of data need to be captured and integrated, and companies will need to find ways to turn huge amounts of data into focused insights.

Bit Stew, from GE Digital, recently commissioned a survey of top IT execs to see if their respective companies were ready for the IIoT.

The survey found that only 30% of companies are currently early adopters of the IIoT, while the other 70% are still in the planning phase. Perhaps more importantly, top IT execs identified the potential barriers to their companies adopting the IIoT, as well as the opportunities that the IIoT can unlock for their operations:

Opportunities

  • 80% of senior IT executives view improving operating efficiency and uptime as the top benefits that IIoT will bring.
  • Other benefits identified: improved operating costs, better uptime, improved asset performance management, and knowledge transfer in the workplace.
  • Larger organizations (1,000+ employees) found improving uptime to be a more compelling benefit than smaller organizations.
  • 70% say that having proven capabilities for data modeling and mapping were more important for a IIoT platform than any other feature.

Barriers to Adoption

  • 64% of senior IT executives said that integrating data from disparate sources and formats, and extracting business value from that data, is the biggest challenge the IIoT presents.
  • Meanwhile, 36% say limited access to the right skills and expertise is the problem.
  • Larger organizations (1,000+ employees) were more likely to struggle with traditional database management and analytics tools (34% vs 12%).
  • 87% say that the overwhelming volume and veracity of data will result in losing valuable business insights.
  • 33% say that businesses without a data management strategy will become marginalized, obsolete, or disappear.

Why is industrial data so complicated?

Industrial data comes from a variety of source types and is often messy. Combine this with its complexity, and that it comes in massive volumes and varied frequencies, and the situation is quite a quagmire for any aspiring adopter.

To enter a truly connected world where data about everything is analyzed instantaneously on an industrial scale, we must first solve these issues around data. It’s only then that the IIoT will show its true potential for business.

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Visualizing AI Patents by Country

See which countries have been granted the most AI patents each year, from 2012 to 2022.

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Visualizing AI Patents by Country

This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.

This infographic shows the number of AI-related patents granted each year from 2010 to 2022 (latest data available). These figures come from the Center for Security and Emerging Technology (CSET), accessed via Stanford University’s 2024 AI Index Report.

From this data, we can see that China first overtook the U.S. in 2013. Since then, the country has seen enormous growth in the number of AI patents granted each year.

YearChinaEU and UKU.S.RoWGlobal Total
20103071379845711,999
20115161299805812,206
20129261129506602,648
20131,035919706272,723
20141,278971,0786673,120
20151,7211101,1355393,505
20161,6211281,2987143,761
20172,4281441,4891,0755,136
20184,7411551,6741,5748,144
20199,5303223,2112,72015,783
202013,0714065,4414,45523,373
202121,9076238,2197,51938,268
202235,3151,17312,07713,69962,264

In 2022, China was granted more patents than every other country combined.

While this suggests that the country is very active in researching the field of artificial intelligence, it doesn’t necessarily mean that China is the farthest in terms of capability.

Key Facts About AI Patents

According to CSET, AI patents relate to mathematical relationships and algorithms, which are considered abstract ideas under patent law. They can also have different meaning, depending on where they are filed.

In the U.S., AI patenting is concentrated amongst large companies including IBM, Microsoft, and Google. On the other hand, AI patenting in China is more distributed across government organizations, universities, and tech firms (e.g. Tencent).

In terms of focus area, China’s patents are typically related to computer vision, a field of AI that enables computers and systems to interpret visual data and inputs. Meanwhile America’s efforts are more evenly distributed across research fields.

Learn More About AI From Visual Capitalist

If you want to see more data visualizations on artificial intelligence, check out this graphic that shows which job departments will be impacted by AI the most.

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