Embedded Systems Trends and Technologies

Author photo: Dick Slansky
ByDick Slansky
ARC Report Abstract

Executive Overview

The overall embedded systems market has evolved considerably in the last few years.  This includes the technology and industries served.  With the advent of IoT and the Industrial IoT (IIoT), embedded systems technology has become an enabler for the rapidly expanding world of smart and connected IoT ecosystems.  The broad, diverse, and highly fragmented embedded systems market consists of software, development platforms, and hardware.  More industries, products, and services than ever now rely on embedded systems. The industrial market for embedded systems includes communications, automotive, aerospace, consumer electronics, military systems, along with industrial controls and other sectors, including smart cities.

An embedded system is typically some combination of hardware and software, either fixed in function or programmable.  An embedded system could be designed to support a specific function or functions within a larger system.  Examples include industrial control systems and machines, automobiles, military systems such as avionics and weapons system, medical equipment, consumer products, smartphones, and building automation.

For simple, high-volume embedded devices for the consumer market, the embedded system cost could be 99 percent hardware and 1 percent software.  But for highly specialized, low-volume embedded systems used for aircraft, automobiles, or highly reliable industrial controls, the software could represent 95 percent of the embedded system cost when testing and compliance to standards on complex applications are included.  A further complication is that there is no clear boundary between embedded systems and computers.  Even today, there is some debate about whether a smartphone or a smart IoT gateway is an embedded system or a standalone computer.  Where conventional IoT gateways collect wireless sensor data and push it to the cloud, new smart IoT gateways and edge devices can support LANs, WANs, and general-purpose computing applications such as analytics or process control.

The hardware components of the embedded systems market include silicon, printed circuit boards, firmware, target devices, etc.  Software elements include development platforms, real-time operating systems (RTOS), testing, etc.  And, of course, the overall market for the devices and machines these embedded systems empower is much larger.

The overall embedded systems market has evolved considerably in the last few years.  This includes the technology and industries served.

Embedded devices are typically powered by software integrated with hardware such as systems on a chip (SoC), field-programmable gate arrays (FPGA), an integrated circuit (IC) designed to be programmed by an embedded developer for a specific function, and other firmware variations.  This makes it difficult to separate software and hardware completely.  Embedded systems suppliers in this market could include those that only provide software, such as development and testing tools and real-time operating systems (RTOS); and those that also provide FPGA, SoC, and other firmware products. 

While embedded systems are a very mature technology overall, with the steady advancement of new and more powerful processors, the technology now enables the next-generation of intelligent devices, machines, equipment, and factories.  Embedded systems represent key enabling technology for the smart, connected products, machines, and systems that comprise the Industrial Internet of Things (IIoT) and support the overall digital transformation of industry.

One of the major trends in the embedded sector is the emergence of intelligent edge devices that will help enable industrial production systems and process plants to become part of the digital enterprise.  Embedded intelligence in sensors and other metrology devices will allow data to be accessed, aggregated, and analyzed to power advanced analytics, enabling production systems and equipment to become part of the IIoT ecosystem and the digital twin.  These are emerging as key enabling technologies to help optimize the asset lifecycle, particularly the operations and maintenance phase.

To address the business opportunity, both cloud and edge infrastructure technology providers need to continue to scale to support literally billions of sensors and tens of thousands of smart systems.  The edge devices must be both connected and intelligent.  The overall embedded systems market will see significant growth because of the huge demand for intelligence at the edge.  The ongoing evolution of IIoT ecosystems and the steady progress of industrial automation to cyber-physical systems based on predictive and prescriptive analytics will eventually lead to autonomous and self-healing systems.  ARC believes this will be a leading industry driver for embedded systems’ growth.

Embedded Systems in the Industries

Embedded systems have been a staple technology in industries like aerospace & defense, automotive, medical devices, communication, and industrial automation for decades.  As processor architecture evolved and more computing power could be embedded in systems and devices, the intelligence and capabilities of these systems increased exponentially.  This has allowed the products that have traditionally used embedded systems to become more intelligent and robust, and enabled products in other industries (consumer goods, appliances, sporting goods, etc.) to become smart and connected.  Embedded systems are becoming an integral component of almost everything in our lives.


Automotive applications currently represent the largest use of embedded systems and will likely remain the biggest portion in the coming years.  In automotive, embedded systems are utilized for infotainment, safety, driver awareness, maintenance, and overall system control of the vehicle.  Expanding requirements for vehicles with advanced navigation, driver assist, and vehicle-to-street communications capabilities will only increase demand for embedded systems. Moreover, intelligent systems control is expanding with the emergence of hybrid electric vehicles (HEV) and electric vehicles (EV).

Additionally, the emerging generation of fully autonomous vehicles will require highly intelligent systems of systems; far more complex than the embedded systems in today’s vehicles. Computing systems in these vehicles will need to run multiple complex artificial intelligence (AI) software and systems for navigation, road and vehicular awareness, traffic patterns, pedestrian awareness, risk awareness and assessment, and so on.  A new generation of processors is being developed for embedded systems to meet these computational and intelligence requirements.

Intelligent Embedded Systems for Automotive

When the topic of AI in the automotive industry is discussed, the first thing that comes to most people’s minds is autonomous vehicles.  Without question, developing driverless cars is a very active area of research and the technology will become a viable component of transportation in the future and possibly the near future.  However, today’s reality is that cognitive learning algorithms are being used mainly to increase efficiency, safety, and add value to processes revolving around traditional, manually driven vehicles.  

Before the automotive industry is ready to let AI “take the wheel,” it first wants to put it in currently produced cars with lots of driver-assist technology. AI lends itself very well to powering advanced safety features for connected vehicles. The driver-assist functions embedded into the vehicles coming off production lines today are helping drivers become comfortable with AI before the vehicles become completely autonomous.

By monitoring dozens of on-board sensors, AI can identify dangerous situations, brake automatically, and take control of the vehicle to avoid an accident and detect and alert the driver of other vehicles and hazards around them.

One area where AI is currently in use for the automotive customer is AI-based cloud services for predictive maintenance.  Unlike conventional vehicles, connected vehicles can do much more than alert the driver with check-engine lights, and low-tire-pressure warnings.  In many of the latest models, embedded AI algorithms monitor hundreds of sensors and can detect problems before they affect vehicle operation.  By monitoring literally thousands of datapoints per second, AI can spot minute changes that could indicate component malfunction or failure.


Healthcare is one of the fastest developing applications for embedded systems. For example, handheld and portable therapeutic equipment and devices and devices for monitoring vital signs make broad use of embedded systems.  And with small embedded systems that monitor heart rate or identify a blockage in an artery, embedded technology has also moved into intricate surgical procedures.

While the physical size of the semiconductors, processors, and chips in embedded systems used in healthcare decreases, we’re also seeing an exponential increase in intelligence and functionality.  This will enable a new generation of medical devices that will be able to function and intervene inside parts and organs of the human body in new and innovative ways. Tiny, but powerful devices will be able to monitor and determine the state and condition of multiple patients remotely through mobile devices connected to a network-based diagnostic center.

Consumer Electronics

Consumer electronics has been a major market for embedded systems for decades, but this market is taking on new significance with the advent of IoT.  A new design criterion is needed for smart connected products and embedded intelligence has become a major component.  Entrepreneurial engineers will likely incorporate new types of sensors and software into the products they design.

The value of connecting machines and assets in factories, plants, and infrastructure has been well established, particularly as this relates to reduced unscheduled downtime and optimizing operations.  In turn, connecting consumer products (smart phones; heart rate monitoring devices; smart home appliances, lighting, security, etc.) to track, monitor, control, and adapt will add significant value.  This applies equally to the user of the product, but also to the service life of the product, future designs that will improve the product, and – where applicable – to the larger systems that these products comprise.

Building Automation

Automation systems for smart buildings and HVAC utilize embedded software and hardware and the sector and should develop rapidly in the coming years.  As we move into the era of smart buildings and smart cities, embedded intelligence will be an integral component of these smart systems. Building automation has been based primarily on monitoring and maintaining environmental conditions, lighting, and access control.  As the systems become smarter, smart building functionality will likely extend into predictive and prescriptive systems that determine the optimal conditions. Ultimately, the goal is to move to completely autonomous and self-healing systems.  These systems will be based on AI and machine learning, all predicated on embedded intelligence.  The smart building industry has embraced the concept of the digital twin, using intelligent sensors to merge physical operations with virtual engineering models.


Table of Contents

  • Executive Overview
  • Embedded Systems in the Industries
  • Trends and Technologies in Embedded Systems
  • Conclusions


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