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Novel Design Approaches in Embedded System Market to Penetrate Industrial Automation Applications

Embedded Systems Market

Industrial automation empowered by smart IoT encompasses a vast appetite for next-gen manufacturing. Product developments in the industrial IoT (IIoT) ecosystem have moved jauntily on the back of this trend. The evolution has circumscribed the uptake of high-volume embedded devices in the path. Thus, growing ubiquity of embedded systems has set tone for embedded IoT world.

Embedded systems typically combine hardware and software in amazing ways, paving way to numerous new automation technologies in industries. These have become a key framework for anything that use smart chip designs, ranging from specialized ones in aerospace and defense, medical devices to not so niche ones in automotive and consumer devices. The technology has grown rapidly to meet the needs of explosion of data in IoT gateways. Several exciting vistas for the digital economy in general have emerged from the deployment of embedded systems.

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High-volume consumer applications to capture value in future

From smartphones to smart cities, the embedded systems market is bristling with opportunities. The advent of programmable processors and advances in real-time operating systems are fueling the growth prospects. Per a recent projection in a report by a business intelligence firm, the opportunities in the market will climb to US$338.34 bn by 2021-end.

In recent years, embedded systems have gotten as complex as one can think of. Numerous technological trends reinforce the transition, broadly novel integration approaches. Businesses aspiring to make a mark in IIoT have braced up for the opportunity emanating from the new level of hardware-software trade-offs in embedded systems.

One telling case in point is the use of the adoption state-of-the art process technologies and the tools to design emerging products for embedded systems market. These systems have raised the expectations for industries in automating and controlling their operational processes, reduce the underlying cost, and manage safety.

Scope of SoC designs expanding kaleidoscope

Topping the list of emerging processing technologies in the embedded systems market is System-on-Chip (SoC) designs, which when engineered may lead to development of real-time systems. These designs are motivated by the need for boosting the performance of the processor and lowering the energy consumption and costs. In the foreseeable future, this is likely to underpin MEMS-based sensors and lab-on-a-chip, bringing transformative potential to smart manufacturing and medical sector and life sciences research.

Other lucrative trends likely to attract steady investments over the years are field-programmable gate arrays (FPGA), firmware products, and real-time operating systems (RTOS). The entire architecture of IoT has brought flexibility to spur new avenues in next-gen factory automation. Next-gen factory automation will spur integration of embedded systems in machines, equipment, devices, making them more connected.

The need for future machine learning models for self-driving cars present a vast scope for them, for example. The use of embedded systems in connected automotive systems has already proliferated, found in infotainment, and sensing technologies for telematics.

Home automation in particular are increasingly realizing the incredible potential SoC embedded technology. Advances in wireless technologies for home automation has already fueled this trend in a big way. A case in point is IoT embedded vision system which is likely to open new vistas in smart factories. 

Machine learning companies to whet their edge in ‘edge computing’

However, with millions of sensors and connected systems the IoT framework includes, one can’t make the enormous data management an afterthought. From here has stemmed the tide toward edge computing—a key advancement in processing capabilities of all these data. Its tete-a-tete with cloud computing has started building up vast revenue streams for players in the embedded systems market.

Machine learning companies in recent years have been putting their bets in edge computing. A number of edge devices will incorporate artificial intelligence and feature deep learning applications. ‘Connect’ with millions of sensors and ‘smartness’ to cost-efficiently manage data with the cloud both are attracting stakeholders. Interestingly, these salient features of edge computing make embedded system developers to whet their edge in the IIoT ecosystem 

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