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The Global Market for Intelligent Video Analytics 2018 to 2023

The Global Market for Intelligent Video Analytics 2018 to 2023

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.

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
List of Charts and Figures
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

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