Overcoming the Challenges of Edge Computing in IIoT

By GUEST BLOGGER: JOHN YOUNES

Category:
Industry Trends

The benefits of Industrial Internet of Things (IIoT) projects are numerous – they can improve manufacturing processes, increase revenues, reduce costs, optimize assets, improve business decisions, and more. Many companies want to take advantage of the value IIoT offers to improve their business, but they do not know how to undergo a digital transformation quickly and in a cost-effective manner to take advantage of the vast amounts of data available at the edge. 

Many companies lack the in-house expertise to deploy an IIoT project.  They don’t know how big the project will become, how to bring together disparate systems, how to collect data from varied assets in real-time, and they can’t predict how the project may grow and change over time.  Several challenges await those who want to embrace Industrial IoT but don’t think things through carefully – challenges for which traditional IoT platforms do not have effective solutions.

The first challenge firms working to embrace Industrial IoT will find is figuring out how the solution will communicate with all of the different legacy controllers and devices found on the factory floor. They all utilize one protocol or another for communication, and data formats will not be standard across the different pieces of equipment. There isn’t a standardized approach for connecting industrial devices, and there isn’t going to be one anytime soon.

The second challenge, and quite possibly the most important one, is security. There are many possible vulnerabilities in IoT solutions. The six main levels of security that need to be implemented are:

  • connecting to devices,
  • transporting data,
  • isolating devices,
  • handling data-at-rest,
  • sending commands and controlling devices, and
  • updating systems.

The third challenge is management of an IoT solution and how to scale as the business requires with increased reliability. The solution should be future-proof, allowing for change without requiring a whole new system.  Without a centralized portal or management interface, it is extremely difficult to manage devices, security, and data collection for the many different types of industrial devices out in the field. There must be a complete management UI that encompasses the ability to host drivers for connectivity via edge gateways, with the ability to manage devices and deploy applications and analytics at the edge.

There are several considerations for scaling distributed solutions at the edge including:

  • gateway device management,
  • industrial driver and connectivity management,
  • edge processing and filtering of data at scale
  • a centralized dashboard for a complete view and management of data and devices,
  • running analytics applications at scale at the Edge and Cloud,
  • achieving cloud connectivity at scale,
  • and security management.

The fourth challenge is utilizing the data by running various applications at the edge. Enterprises must have a mechanism to install, update, and manage applications for a large number of edge devices at once. Having the ability to run applications like complex analytics, anomaly detection, machine learning tools and custom algorithms at the edge is extremely beneficial for saving cloud and bandwidth costs for an IoT implementation. Without having a mechanism to control and manage this process for a large number of gateways at once, it becomes nearly impossible to enable this kind of analysis and real-time control loop.

IoT Platforms Fill the Gap

Platforms are largely accepted as the solution to these IIoT challenges for their simplicity, built-in security and interoperability with varied legacy devices.  IIoT Edge platforms fill the gap between old and modern equipment – lying between physical devices and the end-user software application such as predictive analytics.

Once Industrial firms decide exactly what data they want to capture and how they will use it on the back-end, they should look for a platform that matches up with their needs.  For instance, they should choose an Edge computing platform that can be installed on their gateway or industrial PC of choice, which includes components for data storage, complex event processing, analytics, data filtering, cloud connectivity and overall management of the solution and deployment.

The ideal IIoT platform can “speak the many languages” of IIoT protocols.  An existing library of downloadable applications enabling gateway-based-processing without any extra coding can save a lot of time and money.  Also key to a successful implementation is the ability to manage edge devices remotely from the cloud, and store data in a central location for analytics and visualization.

IIoT platforms simplify the process, using one software to manage a marketplace of applications and industrial drivers to enable gateways to interact with machines and legacy equipment. With a secure edge-level solution to connect to nearly all industrial devices and systems, manufacturers can liberate, process and integrate the data from the factory floor into the cloud or on-premises enterprise systems in a modern and flexible way.

About Your Guest Blogger:

Edge Computing .jpgJohn Younes, co-founder and COO of Litmus Automation. Litmus was founded in 2014 and since then has made incredible strides in the Industrial IoT industry.

 

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