智慧型視訊分析的全球市場 (2018-2023年):影音監控 & 分析上人工智能 (AI)的影響是什麼?

The Global Market for Intelligent Video Analytics 2018 to 2023 - What Will Be the Impact of Artificial Intelligence on Video Surveillance & Analytics?

出版商 Memoori Business Intelligence Ltd. 商品編碼 699019
出版日期 內容資訊 英文 144 Pages; 8 Charts & Tables
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智慧型視訊分析的全球市場 (2018-2023年):影音監控 & 分析上人工智能 (AI)的影響是什麼? The Global Market for Intelligent Video Analytics 2018 to 2023 - What Will Be the Impact of Artificial Intelligence on Video Surveillance & Analytics?
出版日期: 2018年09月08日內容資訊: 英文 144 Pages; 8 Charts & Tables

本報告提供全球智慧型視訊分析市場調查,提供人工智能技術對AI技術到智慧型視訊分析解決方案的影響,影音監控系統·視訊分析軟體的市場規模,需求 & 供給面的課題,流通管道,競爭情形,及投資趨勢等相關的系統性資訊。



第1章 簡介

第2章 AI技術與其對智慧型視訊分析解決方案的影響

  • AI的概況 - IoT,巨量資料 & 區塊鏈
  • AI晶片技術的多樣化 & 新應用的開拓
  • AI晶片技術的開發 - 機器學習 & Deep學習
  • Deep學習及其演算法的優點
  • 對AI視訊分析的需求擴大

第3章 影音監控系統的市場規模 & VMS軟體

  • 影像監視設備的市場規模·預測
  • 視訊管理軟體系統的市場規模·預測

第4章 視訊分析軟體的市場規模 & AI視訊分析軟體的轉變

  • 視訊分析軟體的市場規模
  • AI視訊分析的適用方法
  • AI視訊分析的全球市場

第5章 供給面 & 競爭情形的評估

  • 全球主要相機供應商
  • 全球主要VMS供應商
  • 全球主要視訊分析供應商
  • 全球主要AI晶片廠商

第6章 需求 & 供給面的課題的評估

  • 視訊分析的需求
  • 克服供給面的課題
  • 適合AI視訊分析的主要垂直產業
  • 連接AI - IoT - 區塊鏈
  • AI視訊分析軟體可以提供嗎?

第7章 AI視訊分析解決方案的流通管道

  • 通過視頻監控網絡
  • 雲端

第8章 資金:AI技術競爭中的投資 & 智慧財產權

  • AI晶片 & 軟體的資金 & 投資
  • AI專利是第3快速成長的類別

第9章 風險投資正在為人工智能投入大量資金

  • AI & 機器學習的企業投資
  • 中國投資者為AI解決方案注入數十億

第10章 M&A - 策略性聯盟

  • 策略性聯盟
  • M&A



This Report is Our 1st Detailed Assessment of the Potential Impact Artificial Intelligence will have on Video Surveillance & Analytics.

Video analytics has eaten a few free lunches over the last 15 years. Whilst it has certainly added some value to video installations, there has been much debate about exactly 'how intelligent' the technology really is and whether it provides satisfactory ROI. But in 2018, there is now a growing belief that video analytics could finally move beyond what has been achieved through conventional rule based systems.

This is due in large part to major advances in semiconductor architecture, which is enabling much faster processing; Empowering deep learning and machine learning algorithms to analyze data many times faster than was previously possible. Venture capitalists are now pouring billions of dollars into financing Artificial Intelligence (AI) chip and analytic software companies. Indeed while researching this report, we identified 128 companies across the world that are now in some way helping (hardware & software) to deliver AI video analytic solutions.

There is still much to be done in perfecting the technology and getting it to market, but these 'new tools' have opened up the opportunity to bring AI products to the video analytics market potentially revolutionizing its performance and capability. And if it can deliver, it will further drive demand for intelligent video surveillance, not just for new projects but open up a vast latent potential for retrofitting millions of existing camera installations.


  • What is the market worth now? We have defined AI Video Analytics as a solution that is running deep learning algorithms on a platform that is most likely to be built on a GPU chip architecture. These solutions are very much in their embryonic stage and our best estimate is that global sales of AI Video Analytic solutions in 2017 was only around $115 million, much of this being installed in China on Safe City projects.
  • Video Surveillance systems generate vast amounts of data that is sadly not being utilized properly. There is huge potential to maximize the value of this data by converting it from "dumb to actionable". The material is already out there just waiting to be mined. New chip architectures combined with AI video analytics software when put to work on these gargantuan volumes of data should improve the security, safety and performance of people, buildings and the business enterprise and at the same time provide a major boost to the Video Surveillance Ecosystem.
  • Current law enforcement systems are increasingly unable to cope with the sheer volume of surveillance material captured and stored every day. This is only set to rise, with the population of video cameras increasing by at least 12% per year. These video streams will only ever be useful if processes to search and analyze the mountain of data keep pace. As it stands today vital information is missed because the vast majority of video is simply never viewed.


In order to both size the potential market and future for intelligent video analytics software, in this report we also establish the size of the Video Surveillance equipment business, how it is organized and then focus deeper into the Video Management Solutions (VMS) business as this is where current analytic software for the video surveillance business is most often applied. Today most of the software used falls outside our definition of being "AI Video Analytics" but in the future it will be an inextricable part of it. We therefore review the video surveillance and the VMS business in order to make a serious attempt to forecast the demand for the AI Video Analytics market.

We have identified some 128 companies that are currently active in supply chain for AI Video Analytics. New companies are being added to this list almost daily and we cannot claim that our list is fully comprehensive. Nvidia has emerged as the early leader in AI chips and is particularly strong in video analytics. Nvidia's edge is that its PC gaming processors (GPUs) can be scaled up to handle AI software, thanks to their "parallel processing" circuitry which can handle complex multiple tasks.

China has publically announced its government strategy to dominate AI technology. Its Internet giants like Baidu, Alibaba Group Holdings and Tencent Holdings are pouring money into AI research. China produces around 40% of the world's video cameras and consequently will generate massive amounts of raw data to train AI systems in how to make predictions. There is good reason to think China will make breakthroughs in developing computer algorithms for video applications.


  • There are 2 elements to the implementation of video analytics. The first is the task of adding the analytics engines to the various video streams and enabling them. This is relatively simple to achieve. The second part of the implementation, and the part of the process that can be far more time-consuming, is configuring them for accurate performance. Every site is bespoke, and even very similar sites using the same analytic rules may need to deliver very different results, based upon the specific operational requirements. Even with a self-learning system, there may be a need to adjust detection zones and masks, camera angles, perspective settings
  • We believe there are 2 main factors that will determine the future role that the suppliers of the video surveillance market will play. The first is the broad split between the Enterprise market and the SMB market and the 2 methods of applying AI through either the edge or the cloud.
  • In this report, we have detailed some 6 methods of applying AI and deep learning. They all have benefits in particular applications but all to often in the past there has been a failure to take into account the need to simplify the installation and configuration and more importantly satisfy the buyer that the system is reliable and robust.

Starting at only USD $1,750 for a Single User License, this report provides valuable information into how Video Surveillance and IT companies are developing their businesses through Investment, M&A and Strategic Alliance.


The Information & Data contained in this Report will be of Value to all those Engaged in Managing, Operating and Investing in Video Surveillance companies (and their advisors) around the world. In particular those wishing to understand exactly how Artificial Intelligence is impacting the business, will find its contents particularly useful.

Table of Contents


The Executive Summary

1. Introduction

2. AI Technology and its impact on Intelligent Video Analytics Solutions

  • 2.1 The Panorama of AI - IoT, Big Data & Blockchain
  • 2.2 AI Chip Technologies Diversify & Open up New Applications
  • 2.3 The Development of AI Chip Technology - Machine Learning & Deep Learning
    • 2.3.1 The Development of AI Chip Technology
    • 2.3.2 Machine Learning & Deep Learning
  • 2.4 The Advantages of Deep Learning and its Algorithms
    • 2.4.1 Deep Learning
    • 2.4.2 Start "Shallow" go "Deep"
    • 2.4.3 "Artificial Aspects" to "Aspect Learning"
    • 2.4.4 Key Factors of Deep Learning
    • 2.4.5 Application of Deep Learning Products
    • 2.4.6 The Cost of Deep Learning
    • 2.4.7 Spiking Neural Networks
  • 2.5 There is a Growing Necessity for AI Video Analytics

3. Market Size of Video Surveillance Systems & VMS Software

  • 3.1 Market Size of Video Surveillance Equipment 2017 & Forecast to 2022
    • 3.1.1 Implications of Using 2D Cameras for AI Analytics
    • 3.1.2 Implications of Using 3D Cameras
    • 3.1.3 Implications of Using Thermal Cameras
  • 3.2 Market Size of Video Management Software Systems 2017 & Forecast 2022

4. Market Size of Video Analytic Software & Transition to AI Video Analytics Software

  • 4.1 Market Size of Video Analytic Software 2017
    • 4.1.1 Video Analytic Software about to reach the Inflection Point
    • 4.1.2 Why Video Analytic Software has an immense Growth Potential
    • 4.1.3 Traditional Video Analytic Algorithms Lack Sophistication
  • 4.2 How Will AI Video Analytics be Applied
    • 4.2.1 Add on Camera Analytics
    • 4.2.2 Analytics Appliance / Encoder
    • 4.2.3 Cloud Analytics
    • 4.2.4 Embedded Camera Analytics
    • 4.2.5 Embedded DVR / VMS Analytics
    • 4.2.6 Server Based Analytics
  • 4.3 The World Market for AI Video Analytics

5. Assessing the Supply Side & Competitive Landscape

  • 5.1 The Worlds' Leading Camera Suppliers
  • 5.2 The Worlds' Leading VMS Suppliers
  • 5.3 The Worlds' Leading Video Analytic Suppliers
  • 5.4 The Worlds' Leading AI Chip Manufacturers
    • 5.4.1 AI Semiconductor Chips
    • 5.4.2 Where are we at Today in Applying AI Technology
    • 5.4.3 Challenges in Applying AI Technology
    • 5.4.4 Challenges Running AI at the 'Edge' of Networks

6. Evaluating the Demand & Supply Side Challenges

  • 6.1 Demand for Video Analytics
  • 6.2 Overcoming the Supply Side Challengers
  • 6.3 Leading Verticals for AI Video Analytics
    • 6.3.1 How Intelligent Video Can Make Smart Cities See
    • 6.3.2 Transport goes for AI Video Analytic Solutions
    • 6.3.3 Retail Buildings go for AI Video Analytic Solutions
    • 6.3.4 Facial Recognition Analytics Moves to the Edge
  • 6.4 Connecting AI - IoT - BlockChain
  • 6.5 Can AI Video Analytics Software Deliver?

7. Channels of Distribution for AI Video Analytic Solutions

  • 7.1 Through the Video Surveillance Network
  • 7.2 In the Cloud

8. Funding - Investment & Intellectual Property in the Race for AI Technology

  • 8.1 Funding & Investment in AI Chips & Software
  • 8.2 AI Patents 3rd Fastest Growing Category 2013 to 2017

9. Venture Capital is Investing Enormous Funds in AI

  • 9.1 Investment in AI & Machine Learning Companies
  • 9.2 Chinese Investors Pour Billions into AI Solutions

10. Mergers & Acquisitions - Strategic Alliances

  • 10.1 Strategic Alliances
    • 10.1.1 IBM - Center for Open Source Data and AI Technologies in San Francisco
    • 10.1.2 Nvidia and ARM Partner for Chipmakers to Embed Deep Learning
    • 10.1.3 Amazon Deep Learning Partnership With AgentVi
    • 10.1.4 Google & Baidu Spearhead MLPerf
  • 10.2 Mergers & Acquisitions
    • 10.2.1 Google and Apple's Global Acquisitions
    • 10.2.2 Facebook's Computer Vision Collection
    • 10.2.3 Qualcomm
    • 10.2.4 Intel
    • 10.2.5 Canon Acquires Briefcam
    • 10.2.6 Motorola Acquires Avigilon
    • 10.2.7 Nortek Security & Control Acquires IntelliVision Technologies Corp


  • Table 5.1 - Directory of AI Semiconductor Specialist & Video Analytic Suppliers 2018


  • Fig 2.1 Machine Learning & Deep Learning Capability
  • Fig 3.1 World Sales of Video Surveillance Products 2017 - 2022 ($b)
  • Fig 3.2 World VMS Market for Video Surveillance 2013 - 2022 ($m)
  • Fig 4.1 The World Market for AI Video Analytics Market 2017 - 2022 ($m)
  • Fig 5.1 Performance of Established Players / New Ventures / Challengers / Leaders in the Video Surveillance Camera Market 2017
  • Fig 5.2 Performance of Established Players / New Ventures / Challengers / Leaders in the VMS Market 2017
  • Fig 8.1 US Machine Learning Patent Applications in 2017 by Company


3VR | AI Tech | ABEJA | ACIC | ACTi | Agent VI | Aimetis | Aitek | AllGoVision | Amazon | Ambarella | Anviz Technology Co Ltd | AnyVision | Aventura | Avidbeam | Avigilon | Axis Communications | AxxonSoft | Ayonics | Beijing Impower Tech | Boulder AI | Bosch | BrainChip Holdings Ltd | Briefcam | Camio | Cambricon Technologies | Cerebras Systems | Checkvideo | Cisco | Citilog | Cognimatics | Davantis | Dahua | Deep Glint | DeepMind | Deep Science | Deep Sentinel | Delopt | Detec | Digital Barriers | Disney Research | DVTel | Element AI | Emza | FacebookAI Research (FAIR) | Flame Analytics | FLIR | Foghorn Systems | Foxstream | GiantGray | Genetec | Gorilla Technology Group | Graphcore | Hailo | Hanwha Techwin | Hitachi Vantara | Hikvision | Honeywell | Huawei Technologies | IBM | i2vsys | iCetana | IDIS | Intellivix | IndigoVision | InPixal | Instek Digital | IntelliVision | Intel | Interlogix | intuVision | iOmniscient | IPS | Ipsotek | IronYun | ISS | Jemez Technology | KiwiSecurity Software | KnuEdge | Levaux IoT | Magenta | Mango DSP | Megvii Face++ | Microsoft | Milestone | Mindtree | Mirasys Ltd | NEC Corporation | Netavis | Neurala | Ngaro Intelligent Solutions | NUUO | Nvidia | Objectvideo Labs | OpenAI | OpenALPR | Parking Spotter | Promise Technologies | Prism Skylabs | PointGrab | PureTech Systems | Qognify | RetailFlux | Samsung | Sensetime | Sightlogix | Smartervision | Snap FMx | Sony | Sprinx Technologies | Standard Cognition | SWIM.AI | TechnoAware | TensorFlow | Tyco (JCI) | Umbo Computer Vision | Vanderbilt Industries | VCA Technology | Verint | Via:sys | Videonectics Technologies | VIDiCore GmbH | Vaelsys | Viisights | Viseum | Veritone | YITU Technology | XNOR

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