Edge AI Hardware Market - Growth, Trends, and Forecast (2020 - 2025)

出版商 Mordor Intelligence LLP 商品編碼 906963
出版日期 內容資訊 英文 120 Pages
商品交期: 2-3個工作天內
全球邊緣AI硬體設備市場-:成長,趨勢,及預測(2019年∼2024年) Edge AI Hardware Market - Growth, Trends, and Forecast (2020 - 2025)
出版日期: 2020年01月01日內容資訊: 英文 120 Pages




第1章 簡介

  • 調查成果
  • 調查的假設
  • 調查範圍

第2章 調查方法

第3章 摘要整理

第4章 市場動態

  • 市場概況
  • 市場成長及阻礙因素概要
  • 市場成長要素
  • 市場阻礙因素
  • 產業價值鏈分析
  • 產業的魅力-波特的五力分析
    • 新加入廠商的威脅
    • 買主/消費者談判力
    • 供應商談判力
    • 替代產品的威脅
    • 產業內的競爭

第5章 市場區隔

  • 各處理器
    • CPU
    • GPU
    • FPGA
    • ASIC
  • 各設備
    • 智慧型手機
    • 相機
    • 機器人
    • 穿戴式
    • 智慧喇叭
    • 智慧鏡子
    • 其他
  • 各終端用戶產業
    • 政府
    • 家電
    • 不動產
    • 汽車
    • 運輸機關
    • 醫療保健
    • 製造業
  • 各地區
    • 北美
    • 歐洲
    • 亞太地區
    • 南美
    • 中東及非洲地區

第6章 競爭情形

  • 企業簡介
    • Intel Corporation
    • NVIDIA Corporation
    • Samsung Electronics Co., Ltd.
    • Huawei Technologies Co., Ltd.
    • Google Inc.
    • MediaTek Inc.
    • Microsoft Corporation
    • Xilinx Inc.
    • Imagination Technologies Limited

第7章 投資分析

第8章 市場機會及未來趨勢


Product Code: 66635

Market Overview

The edge AI hardware market is anticipated to witness a CAGR of 20.3% over the forecast period 2020 - 2025. During 2018 it is estimated that about 212 million edge AI hardware was shipped and the figure is expected to reach a billion units by 2020. Rapid growth in the number of edge computing products and services, increasing real-time low latency on edge devices are some of the major influencing factors for the growth of edge AI hardware market. Notably, the need for edge computing in IoT and dedicated AI processors for on-device image analytics are the promising areas of market advancement in the edge AI devices.

  • The possibility of performing AI inference without having to transfer the data has generated huge demand for edge AI Hardware market. With the growing number of edge AI devices, businesses can reduce their operational costs in critical cases where latency and accuracy are much required.
  • Constant connectivity with enhanced performance has generated huge demand for edge AI devices among several industrial applications such as government, consumer electronics, real estate, automotive, transportation, healthcare, manufacturing, and others.
  • The market is anticipated to see a high rate of adoption in the coming years owing to increased privacy and security since the companies need not share private or sensitive data with public cloud service providers, especially in healthcare and consumer sectors. A survey conducted by Cloud Security Alliance (CSA) among 200 IT and IT security leaders identified that 73% of survey respondents listed privacy and security of data as their biggest concern.
  • The dearth of skilled AI professionals is anticipated to obstruct the market growth of edge AI hardware.
  • The market is expected to witness intense competition among the key players and several prominent startups, to capture a share of revenue in edge AI hardware market.

Scope of the Report

The scope for edge AI hardware market primarily includes processors, sensors, cameras that address the need for cognitive computing needs. These devices are used to power and process various AI-based devices. Various types of processors used in edge AI devices include semiconductor products such as central processing units (CPU), graphic processing unit (GPU), field-programmable gate array (FPGA), and application-specific integrated circuits (ASICs).

Key Market Trends

Surveillance Cameras Segment is Expected to Grow at Significant Rate

  • Governmental bodies across the world, are embracing advanced technologies to address the important aspect of ensuring the security and safety of citizens. Surveillance serves to be a key factor in the process. Some of the major devices for edge AI hardware used by government agencies for the purpose includes surveillance cameras and drones.
  • With the ever-increasing population, environmental damage, and criminal activities, cities are facing new challenges each day, and this has resulted in the need for surveillance cameras. These are very much required for the prevention of incidents such as crime, burglary, and vandalism. Besides, governments also use surveillance cameras for enforcement of the law by analyzing the behavior, face recognition.
  • China is at the forefront of installing AI-based surveillance cameras to scan public places to track anomalies in behavior and criminal identification. A recent journal published in the New York Times revealed that the Chinese government had installed around 200 million surveillance cameras across the country in 2018 and is planning to install another 426 million by 2020. The country aims to spot crimes and accidents easily by integrating private and public cameras, to build a nation-wide surveillance network.

Asia-Pacific to be the Fastest Growing Region

  • Asia-Pacific region is expected to experience the highest growth rate in the global edge AI hardware market. The growing penetration of smartphones in China, Japan, India, and South Korea is expected to increase the adoption of AI processor-enabled smartphones. Moreover, the region is also the most significant market for surveillance cameras owing to the tightened control over the Internet and digital communication by the governments in the respective countries.
  • China is the largest market in the region, followed by Japan. Presence of several significant vendors in the automobile, electronics, and semiconductor companies, who are investing significantly in the AI technology, is driving the growth of the edge AI hardware market in the region. During a one-month period between June and July 2018, Beijing Municipal Commission of Economy and Information Technology counted around 4,040 AI companies in China. Besides, the presence of a large number of manufacturing companies makes the region an attractive market for industrial robots that implements AI technology.
  • Wearable devices also play a significant role in the increasing demand for integration with vision processing units to accelerate AI tasks. Cisco Systems estimates that the number of connected wearable devices could reach 1,105 million units by 2022. End-user industries like manufacturing, telecommunications, and automotive have huge potential in the region.

Competitive Landscape

The edge AI hardware market is currently dominated by few players with their technological expertise in AI technology and the global market is expected to be consolidated in nature. Intel Corporation, NVIDIA Corporation, Qualcomm Inc., Samsung Electronics Co., Ltd., Huawei Technologies Co., Ltd., Google Inc., MediaTek Inc., Xilinx Inc., Imagination Technologies Limited, and Microsoft Corporation are some of the major players present in the current market. However, several prominent AI startups like Cambricon Technology, Horizon Robotics, Hailo Technologies, and Habana Labs are expected to compete with the key players, on the AI inferencing side.

  • March 2019 - NVIDIA published Jetson Nano, an edge computing production for machine learning (ML) inferencing. It enables the development of millions of new small, low-power AI systems in embedded IoT applications, including entry-level Network Video Recorders (NVRs), home robots.
  • May 2019 - Kneron, an AI startup focussed on edge AI solutions unveiled 3D artificial intelligence solution and edge AI chip KL520 with n idea to provide AI solutions for the smart home, smart surveillance, smartphones, robots, drones, and IoT devices.
  • September 2018 - Intel in collaboration with Alibaba Cloud launched a Joint Edge Computing Platform. Enterprises would be able to develop customizable device-to-cloud IoT solutions for different edge computing scenarios with the help of the platform, including industrial manufacturing, smart building, and smart community.

Reasons to Purchase this report:

  • The market estimate (ME) sheet in Excel format
  • Report customization as per the client's requirements
  • 3 months of analyst support

Table of Contents


  • 1.1 Study Deliverables
  • 1.2 Study Assumptions
  • 1.3 Scope of the Study




  • 4.1 Market Overview
  • 4.2 Introduction to Market Drivers and Restraints
  • 4.3 Market Drivers
    • 4.3.1 Rapid Growth in the Number of Edge Computing Products and Services
    • 4.3.2 Increasing Penentration of AI in Edge Devices
    • 4.3.3 Increasing Real-time Low Latency on Edge Devices
  • 4.4 Market Restraints
    • 4.4.1 Security Concerns Related to Edge AI Devices
    • 4.4.2 Dearth of Skilled AI Professionals
  • 4.5 Industry Value Chain Analysis
  • 4.6 Industry Attractiveness - Porter's Five Force Analysis
    • 4.6.1 Threat of New Entrants
    • 4.6.2 Bargaining Power of Buyers/Consumers
    • 4.6.3 Bargaining Power of Suppliers
    • 4.6.4 Threat of Substitute Products
    • 4.6.5 Intensity of Competitive Rivalry


  • 5.1 By Processors
    • 5.1.1 CPU
    • 5.1.2 GPU
    • 5.1.3 FPGA
    • 5.1.4 ASICs
  • 5.2 By Device
    • 5.2.1 Smartphones
    • 5.2.2 Cameras
    • 5.2.3 Robots
    • 5.2.4 Wearables
    • 5.2.5 Smart Speaker
    • 5.2.6 Other Devices
  • 5.3 By End-User Industry
    • 5.3.1 Government
    • 5.3.2 Consumer Electronics
    • 5.3.3 Real Estate
    • 5.3.4 Automotive
    • 5.3.5 Transportation
    • 5.3.6 Healthcare
    • 5.3.7 Manufacturing
  • 5.4 Geography
    • 5.4.1 North America
    • 5.4.2 Europe
    • 5.4.3 Asia-Pacific
    • 5.4.4 Latin America
    • 5.4.5 Middle East & Africa


  • 6.1 Company Profiles
    • 6.1.1 Intel Corporation
    • 6.1.2 Huawei Technologies Co., Ltd.
    • 6.1.3 Nvidia Corporation
    • 6.1.4 Advanced Micro Devices, Inc.
    • 6.1.5 Baidu, Inc
    • 6.1.6 Alphabet Inc.
    • 6.1.7 Qualcomm Incorporated
    • 6.1.8 Samsung Group
    • 6.1.9 Apple Inc.
    • 6.1.10 Amazon.com, Inc.
    • 6.1.11 Alibaba Group Holding Limited
    • 6.1.12 Continental AG
    • 6.1.13 Denso Corporation
    • 6.1.14 Robert Bosch GmbH
    • 6.1.15 KALRAY Corporation
    • 6.1.16 MediaTek Inc.
    • 6.1.17 Xilinx Inc