Industrial IoT: The New Frontier

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7 min read

While smart refrigerators, cars, fitness monitors, and even toasters have been widely available to consumers for years, the Internet of Things (IoT) also has a wealth of applications for industrial enterprises in the form of the Industrial Internet of Things (IIoT).

But how can enterprises make the most of IIoT, and how can they overcome the challenges that commonly arise when trying to do so? Let's find out.

What Is Industrial IoT?

Industrial IoT is exactly what it sounds like: a specific class of IoT machines, devices, and systems that work to help industrial enterprises prevent accidents, reduce downtime, and optimize productivity.

From healthcare and agriculture to energy and defense, a wide array of industries have already discovered the benefits of IIoT.

To name just a few examples, oil companies can use oil rig sensors to predict malfunctions and oil spills before they happen; renewable energy companies use IIoT-enabled wind turbines to maximize energy production; and farmers can use drones to monitor their crops and increase their return on investment.

Of course, IIoT is much more than a collection of smart devices and machines. It uses those devices and machines to generate massive amounts of data that must then be processed, analyzed, and stored in order to be effectively leveraged. So, in order to be successful, IIoT must also be supported with a powerful and efficient data system.

What Are the Challenges of IIoT?

As is the case with all technologies, IIoT is not without its challenges. Industrial enterprises are frequently faced with daunting obstacles, such as:

  • Frequent downtime: Oftentimes, IIoT devices and machines are deployed in remote locations with unreliable network connectivity.
  • Network limitations: Intermittent network connectivity isn't the only network-related problem that companies can encounter. Will Ochandarena, our Director of Product Management, says in his article at RFID Journal:

"Due to network limitations, it isn't feasible to send all data to a central location for analysis, so the edge system needs to be able to act independently of the core, while staying in tight synchronization."

  • Limited physical space: Enterprises often struggle to find adequate physical space to house the servers required to process and analyze the amount of data being generated.
  • Compliance and privacy requirements: In many industries, regulations are in place that stipulate where data should reside and how heavily it should be protected. Thus, enterprises need to use IIoT within their industry's regulatory parameters.
  • Legacy systems: Any company trying to harness the power of IIoT simply won't be able to rely on legacy systems. The demand of real-time data transmission and analysis is too great for outdated systems to handle, so investing in new systems can present a financial obstacle.
  • Data silos: To put it bluntly, silos are the enemy of IIoT. Ochandarena explains:

"The issue of data silos actually impacts companies across nearly all verticals, but I would argue it affects the industrial sector the most. Why? Because the data silos that exist in factories and industrial sites … are smaller in size and more limited in capability than those of other industries."</blockquote

So, although IIoT can be a major boon to various companies, it's not enough to simply use it – you have to use it correctly in order to see significant results.

How Does MapR Work With IIoT?

To address the complexities and challenges of IIoT, MapR has designed MapR Edge to fulfill the potential of every aspect of IIoT.

In short, MapR Edge is a fully functional MapR cluster that can run on small form-factor commodity hardware, like Intel NUCs. Each cluster is supported in three to five node configurations, which are outfitted with a full suite of services and capabilities, including:

  • Distributed data aggregation: Consolidates data from edge sites and provides high-speed local processing, which is especially useful for restricted or sensitive data.
  • Bandwidth awareness: Adjusts throughput from the edge to the cloud and/or data center, even with occasionally connected environments.
  • Global data plane: Simplifies application, deployment, and development by providing a global view of all distributed clusters in a single namespace.
  • Analytics: Combines operational decision-making with real-time data analysis at the edge.
  • Unified security: End-to-end IoT security provides authentication, authorization, and access control from the edge to the central clusters and delivers secure encryption on the wire for data communicated between the edge and the main data center.
  • Standard adherence: Adheres to standards including POSIX and HDFS API for file access, ANSI SQL for querying, Kafka API for event streams, and HBase and OJAI API for NoSQL database.
  • Enterprise-grade reliability for five-node edge cluster configurations: Delivers a reliable computing environment to tolerate multiple hardware failures that can occur in remote, isolated deployments.

In a recent DM Radio episode, Jack Norris, our Senior Vice President of Data and Applications, puts it this way:

"A data fabric that can stretch from the edge to centralized processing in a data center or a collection of clouds is very important. We want to inject the intelligence back out to the edge so that we can act very quickly, and that's whether you're talking about medical equipment, oil and gas, or connected cars. It's not just 'how do we pull this sensor data,' but 'how do we understand the context so that we can inject the analytics into the operation.'"

MapR Edge makes that possible by providing secure local processing, fast aggregation of insights on a global scale, and the ability to push intelligence back to the edge.

With MapR Edge, IIoT becomes more than a collection of sensors and silos. Instead, it's a valuable source of data, insights, and predictions that runs like a well-oiled machine and can overcome almost any obstacle that's thrown at it.

Additional Resources:


This blog post was published August 10, 2018.
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