Global Intelligent Video Analytics Market 2018-2023: Evaluating the Demand & Supply Side Challenges

DUBLIN, Sept. 11, 2018 /PRNewswire/ --

The "The Global Market for Intelligent Video Analytics 2018 to 2023" report has been added to ResearchAndMarkets.com's offering.

What will be the Impact of Artificial Intelligence 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, the researchers 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.

Why Do You Need This Report?

• What is the market worth now? The researchers 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 the researchers 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 the video is simply never viewed.

In order to both size the potential market and future for intelligent video analytics software, in this report the researchers 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 the researcher's definition of being AI Video Analytics but in the future, it will be an inextricable part of it. The publisher, therefore, reviews the video surveillance and the VMS business in order to make a serious attempt to forecast the demand for the AI Video Analytics market.

The researchers have identified some 128 companies that are currently active in the supply chain for AI Video Analytics. New companies are being added to this list almost daily and the researchers cannot claim that the researcher's 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 a good reason to think China will make breakthroughs in developing computer algorithms for video applications.

The Report Presents All the Key Facts and Draws Conclusions, so you can Understand the Impact that Artificial Intelligence is having on Video Surveillance and Analytics;

• 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
• The researchers 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, the researchers 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.
• This report provides valuable information into how Video Surveillance and IT companies are developing their businesses through Investment, M&A and Strategic Alliance.

Key Topics Covered:

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

Companies Mentioned

• 3VR
• ABEJA
• ACIC
• ACTi
• Agent VI
• AI Tech
• Aimetis
• Aitek
• AllGoVision
• Amazon
• Ambarella
• Anviz Technology Co Ltd
• AnyVision
• Aventura
• Avidbeam
• Avigilon
• Axis Communications
• AxxonSoft
• Ayonics
• Beijing Impower Tech
• Bosch
• Boulder AI
• BrainChip Holdings Ltd
• Briefcam
• Cambricon Technologies
• Camio
• Cerebras Systems
• Checkvideo
• Cisco
• Citilog
• Cognimatics
• Dahua
• Davantis
• Deep Glint
• Deep Science
• Deep Sentinel
• DeepMind
• Delopt
• Detec
• Digital Barriers
• Disney Research
• DVTel
• Element AI
• Emza
• FacebookAI Research (FAIR)
• Flame Analytics
• FLIR
• Foghorn Systems
• Foxstream
• Genetec
• GiantGray
• Gorilla Technology Group
• Graphcore
• Hailo
• Hanwha Techwin
• Hikvision
• Hitachi Vantara
• Honeywell
• Huawei Technologies
• i2vsys
• IBM
• iCetana
• IDIS
• IndigoVision
• InPixal
• Instek Digital
• Intel
• IntelliVision
• Intellivix
• 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
• PointGrab
• Prism Skylabs
• Promise Technologies
• PureTech Systems
• Qognify
• RetailFlux
• Samsung
• Sensetime
• Sightlogix
• Smartervision
• Snap FMx
• Sony
• Sprinx Technologies
• Standard Cognition
• SWIM.AI
• TechnoAware
• TensorFlow
• Tyco (JCI)
• Umbo Computer Vision
• Vaelsys
• Vanderbilt Industries
• VCA Technology
• Verint
• Veritone
• Via:sys
• Videonectics Technologies
• VIDiCore GmbH
• Viisights
• Viseum
• XNOR
• YITU Technology

For more information about this report visit

https://www.researchandmarkets.com/research/5wx5lw/global?w=5

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