Global Artificial Intelligence for Edge Devices Market 2019 by Company, Regions, Type and Application, Forecast to 2024

SKU ID : GIR- 13599059

Publishing Date : 20-Jun-2019

No. of pages : 120

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  • Artificial intelligence (AI) processing today is mostly done in a cloud-based data center. The majority of AI processing is dominated by training of deep learning models, which requires heavy compute capacity. Artificial intelligence for edge devices means that AI software algorithms are processed locally on a hardware device. The algorithms are using data (sensor data or signals) that are created on the device. A device using Edge AI software does not need to be connected in order to work properly, it can process data and take decisions independently without a connection. In this report, artificial intelligence for edge devices contains software tools, platforms, artificial intelligence chip.

    Scope of the Report:
    Artificial Intelligence for Edge Devices is mainly used for these applications: Automotive, Consumer and Enterprise Robotics, Drones, Head-Mounted Displays, Smart Speakers, Mobile Phones, PCs/Tablets and Security Cameras, and Mobile Phones was the most widely used area which took up about 61.05% of the global total in 2018.
    United States is the largest consumption countries of Artificial Intelligence for Edge Devices in the world in the past few years and it will keep leader position in the next few years. United States market took up about 44.46% the global market in 2018, while Europe was about 19.29%.
    The global Artificial Intelligence for Edge Devices market is valued at 1491.3 million USD in 2018 and is expected to reach 4684.3 million USD by the end of 2024, growing at a CAGR of 25.7% between 2019 and 2024.
    The Asia-Pacific will occupy for more market share in following years, especially in China, also fast growing India and Southeast Asia regions.
    North America, especially The United States, will still play an important role which cannot be ignored. Any changes from United States might affect the development trend of Artificial Intelligence for Edge Devices.
    Europe also play important roles in global market, with market size of xx million USD in 2019 and will be xx million USD in 2024, with a CAGR of xx%.
    This report studies the Artificial Intelligence for Edge Devices market status and outlook of Global and major regions, from angles of players, countries, product types and end industries; this report analyzes the top players in global market, and splits the Artificial Intelligence for Edge Devices market by product type and applications/end industries.

    Market Segment by Companies, this report covers
    Microsoft
    Qualcomm
    Intel
    Google
    Alibaba
    NVIDIA
    Arm
    Horizon Robotics
    Baidu
    Synopsys
    Cambricon
    MediaTek
    Mythic
    NXP

    Market Segment by Regions, regional analysis covers
    North America (United States, Canada and Mexico)
    Europe (Germany, France, UK, Russia and Italy)
    Asia-Pacific (China, Japan, Korea, India and Southeast Asia)
    South America (Brazil, Argentina, Colombia)
    Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

    Market Segment by Type, covers
    Hardware
    Software

    Market Segment by Applications, can be divided into
    Automotive
    Consumer and Enterprise Robotics
    Drones
    Head-Mounted Displays
    Smart Speakers
    Mobile Phones
    PCs/Tablets
    Security Cameras

    Frequently Asked Questions



    This market study covers the global and regional market with an in-depth analysis of the overall growth prospects in the market. Furthermore, it sheds light on the comprehensive competitive landscape of the global market. The report further offers a dashboard overview of leading companies encompassing their successful marketing strategies, market contribution, recent developments in both historic and present contexts.

    • By product type
    • By End User/Applications
    • By Technology
    • By Region

    The report provides a detailed evaluation of the market by highlighting information on different aspects which include drivers, restraints, opportunities, and threats. This information can help stakeholders to make appropriate decisions before investing.
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