Global Edge AI Hardware Market is Expected to Reach USD 1,929.21 Million by 2026 : Fior Markets

Edge AI Hardware Market by Device (Smartphones, Cameras, Robots, Wearables, Smart Speaker, Automotive, Smart Mirror), Processors, Power Consumption, Process, End-User, Region, Global Industry Analysis, Market Size, Share, Growth, Trends, and Forecast 2019 to 2026

Newark, NJ, Jan. 23, 2020 (GLOBE NEWSWIRE) — The global edge AI hardware market is expected to grow from USD 423.34 Million in 2018 to USD 1,929.21 Million by 2026 at a CAGR of 20.9% during the forecast period 2019-2026, according to the new report published by Fior Markets. Rising demand for low latency and real-time processing on edge devices and evolution of AI coprocessors for edge computing are the two major factors contributing to the growth of the market. Further, underlying opportunities for the edge AI hardware market include increasing demand for edge computing in IOT and dedicated AI processors for on-device image analytics.

An edge device is defined as a piece of hardware that monitors data flow at the boundary between two networks. Edge devices function with different roles, depending on what type of device they are, however basically serve as network entry points. Some examples of functions of edge devices are the transmission, routing, processing, monitoring, filtering, translation and storage of data passing between networks. Enterprises and service providers use edge devices. For instance, in March 2019, Alphabet Inc.’s subsidiary Google unveiled a number of new hardware products for AI development. The products include a development board, a USB accelerator, and a 5-megapixel camera.

Rise in demand for faster and efficient edge hardware devices that require lower processing time in AI applications; this factor is expected to act as a driver for the market growth. However, lack of on-device training is the major challenge for the manufacturers which is restraining the growth of the market. Nevertheless, increasing demand for edge computing is anticipated to drive Edge AI Hardware market in forthcoming years.

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Key players operating in the global Edge AI Hardware market include are Videantis GmbH, Qualcomm Technologies, Inc., NVIDIA Corporation, Premier Farnell Limited, Micron Technology, Inc., Alphabet Inc., SecureRF Corporation, Microsoft, Xilinx Inc., Intel Corporation, Huawei Technologies Co., Ltd., SAMSUNG, Apple Inc., Arm Limited, MediaTek Inc., Applied Brain Research, Inc., Horizon Robotics, Cadence Design Systems, Inc., CEVA, Inc., Imagination Technologies Limited; Synopsys, Inc., Thinci; General Vision, Mythic, Adapteva, Inc., Tenstorrent Inc and VeriSilicon Limited among others. To enhance their market position in the global edge AI hardware market, the key players are now focusing on adopting the strategies such as product innovations, mergers & acquisitions, recent developments, joint venture, collaborations, and partnership.

The smartphones segment is dominating the market with the highest market share of 28.90% in 2018

The device segment is classified into smartphones, cameras, robots, wearables, smart speaker, automotive and smart mirror. The smartphones segment is dominating the market in 2018 in 2018. Dedicated AI chip or AI processors were one of the major developments in the smartphone technology last year. Growing demand for real-time speech and voice recognition and analysis, as well as technical advancements in smartphone image recognition is driving the market for AI processors in smartphones.

The CPU segment is dominating the market with the highest market share and valued around USD 199.81 Million in 2018

Processors segment includes CPU, GPU, Asic and others. The CPU segment is dominating the market with the highest share of 47.20% in 2018. CPU is the most commonly used processor for on-device inference in smartphones, smart speakers, and wearables.

More Than 10 W segment is dominating the market with the highest market share of 39.10% in 2018

Power consumption segment is divided into segments such as Less Than 1 W, 1–3 W, 3–5 W, 5–10 W and More Than 10 W. More Than 10 W segment is dominating the market and valued around USD 165.52 Million in 2018.

The inference segment is dominating the market with the highest market share and valued around USD 259.08 Million in 2018

The process segment includes training and inference. The inference segment dominated the market with the highest market share of 61.20% in 2018 due to the development of efficient processors which is driving edge inference market.

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Regional Segment Analysis of the Edge AI Hardware Market

North America (U.S. , Canada, Mexico)
Europe (Germany, France, U.K., Italy, Spain, Rest of the Europe)
Asia-Pacific (China, Japan India, Rest of APAC)
South America (Brazil and Rest of South America)
Middle East and Africa (UAE, South Africa, Rest of MEA)

North America region dominated the global Edge AI Hardware market with USD 174.41 Million in 2018 where as the Asia Pacific region held the second dominant position in the market. North America is dominating the market due to growing dependency on IOT devices, rising need for faster device processing, and high latency due to network congestion. High government funding and strong technical base are also contributing to the growth of the market in this region. Asia Pacific region is growing rapidly in the market as it is a hub of a large number of manufacturing companies. Along with which, there is a strong presence of automobile and electronics and semiconductor companies, in China and Japan which is driving the growth of the edge AI hardware market in APAC.

About the report:

The global Edge AI Hardware market is analysed on the basis of value (USD million) and volume (thousand units). All the segments have been analyzed on global, regional and country basis. The study includes the analysis of more than 30 countries for each segment. The report offers in-depth analysis of driving factors, opportunities, restraints, and challenges for gaining the key insight of the market. The study includes porter’s five forces model, attractiveness analysis, raw material analysis, supply, demand analysis, competitor position grid analysis, distribution and marketing channels analysis.

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