IIoT and the Intelligent Edge Re-defining the Embedded Systems Market

Author photo: Dick Slansky
ByDick Slansky
Category:
Industry Trends

I have been working to get my arms around the embedded systems market for some time now, from the perspective of doing research for a market study that will define this industry, the technology involved, the products and applications, the suppliers, and the users. I quickly realized that this would be no small task, given the very expansive scope of this space and the broad range of hardware, software, and sheer number of variations of devices targeted, and the multiple industries, markets, and businesses involved.

To narrow the scope of this market study I decided to focus on an area that I and my colleagues here at ARC have been concentrating on for some time now: The Industrial IoT and the emergence of connected and intelligent edge devices that will enable and power IIoT. IIoT (at the smart edge device level) remains a major new market for the embedded systems industry. Many suppliers in the ES space maintain that IoT was the natural evolution for ES, and would significantly grow the market. At this juncture in the proliferation of the industrial IoT, it appears that the largest market for ES is in manufacturing, predictive analytics, maintenance and operations for equipment in the field, and the implementation of the digital twin. The more intelligence and functionality that can be placed in the large array of smart sensors, predictive analytics devices in machines, production equipment, and equipment in the field at the point of operations, the more accurate and effective connected ecosystems of the IIoT will be.

The purpose and intent of an ES software study is to focus on ES as a market to support the industrial IoT (IIoT) and the intelligent edge device market. This would include equipment and systems for factory production, process plants, and industrial equipment in the field. Industrial IoT in this context would include smart sensors, industrial controls, industrial gateways and production equipment like machines, PLCs, PACs, CNCs, robotic controls, field devices, drives, actuators, motors, etc.

The embedded software element within this scope would include embedded applications targeted to intelligent edge devices, smart sensors, and other intelligent interface devices within the above described environment. This would also include RTOSs, open source s/w (primarily Linux), firmware, SoC, and development environments, security systems, and network connectivity associated with cloud-based systems for data aggregation and analytics.

Embedded Systems Market Scope

    • Industrial GatewaysEmbedded Systems edge.jpg

    • Device Management

    • Simulation S/W

    • Embedded runtime

    • Communication Protocols

    • Embedded Edge Devices (Intelligent Sensors, etc.)

    • Cloud Services software

If we look at the scope of the embedded systems market primarily in the context of IIoT and the intelligent edge in industrial settings, this represents an important and surging market for ES. Major suppliers in the ES space like Mentor Graphics (Siemens), Wind River (Intel), Microsoft, Green Hills S/W all have business strategies and solutions dealing directly with IIoT and the intelligent edge. By focusing on the scope of embedded systems solutions dedicated to providing technology to enable IIoT and connected and smart edge devices, it serves to place an emphasis on an emerging and important sector of very broad and diverse embedded systems market.

ES is moving rapidly to advanced intelligence technologies like cognitive ES, artificial neural networks (ANNs), deep learning, embedded vision and speech, and embedded machine learning in smart edge devices. The forecast is that in 5-10 years, 50 percent of all smart devices will have cognitive systems, and this includes edge devices for manufacturing and productions systems. This is going to have a significant impact on areas like virtual and augmented reality use in production operations and maintenance, predictive and prescriptive analytics, and the actual implementation of autonomous self-healing systems for industry.

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