cameras and computing for surveillance and security 2020
TRANSCRIPT
From Technologies to Markets
© 2020
From Technologies to Markets
© 2020
Cameras and computing for
surveillance and security 2020
Market and Technology
Report 2020
Sample
22
• Glossary 2
• Definitions 3
• Table of contents 4
• About the author 5
• Companies cited in this report 6
• Scope, objectives and methodology 7
• Three-slide summary 16
• Executive summary 20
• Context 60
o History and applications 61
o How does it work? 64
o From image processing to image analysis 69
o Artificial Intelligence and beyond 85
• Market Forecasts 93
o Methodology 94
o Global number of surveillance cameras in the world in 2019 97
o Global surveillance cameras shipments forecast 101
o Surveillance cameras vendor market share 102
o Global revenues of surveillance cameras and forecast 104
o Technological segmentation of hardware for surveillance 105
o Processing and computing IC shipments forecast 111
o Processing and computing IC revenue forecast 117
o A word on wafer starts for surveillance ICs 122
o Forecasts key points 126
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TABLE OF CONTENTS
• Market Trends 127
o Where to find surveillance? Moving to a smarter world 128
o Smart city 125
o Smart retail 136
o Smart home 142
o Industrial and defense 149
o Conclusion 153
• Technology Trends 155
o Analog vs digital 156
o Analog 161
o Digital 165
o Conclusion 172
• Ecosystem 175
o Ecosystem - Sensors 177
o Ecosystem – OEMs 178
o Chinese camera OEMs’ supply chains 180
o Axis Communications’ supply chain 181
o Ecosystem – Processing and computing 183
o Roadmaps 184
o Computing hardware for AI solutions landscape 189
o Geopolitical concerns, impact of the trade war 190
o The value chain follows the data flow 191
• Conclusion 192
• Annex – Software technologies 196
o Image processing 197
o Image analysis 215
• Yole Développement corporate presentation 223
3
Yohann Tschudi
As a Software & Market Analyst, Dr. Yohann Tschudi is a member of the Semiconductor & Software division at Yole Développement (Yole). Yohann
works daily with his team to identify, understand, and analyze the role of software and computing parts within any semiconductor product, from
machine code to the most advanced algorithms. Following his thesis at CERN (Geneva, Switzerland), Yohann developed dedicated software for fluid
mechanics and thermodynamic applications. Afterwards, he served for two years at the University of Miami (FL, United-States) as an AI scientist.
Yohann has a PhD in High-Energy Physics and a Master’s in Physical Sciences from Claude Bernard University (Lyon, France).
Contact: [email protected]
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ABOUT THE AUTHOR
Biography & contact
44
Hikvision (China), Dahua Technology (China), Axis Communications (Sweden), Bosch
Security and Safety Systems (Germany), Hanwha Techwin (South Korea), Avigilon
(Canada), FLIR Systems (US), Honeywell Commercial Security (US), Panasonic i-PRO
Sensing Solutions (US), Pelco (US), Huawei Technologies (China), NEC (Japan), Tiandy
Technologies (China), VIVOTEK (Taiwan) and Zhejiang Uniview Technologies (China),
OmniVision (US), On Semiconductor (US), Sony (Japan), Ambarella (US), NVIDIA
(US), Qualcomm (US), Intel (US), Rockchip (China), SigmaStar (Taiwan) HiSilicon
(China), SMIC (China), ARM (UK), Xilinx (US), TSMC (Taiwan), and many more…
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COMPANIES CITED IN THIS REPORT
55
• This is the first report on dedicated processing and computing for surveillance and security. Itsobjective is to clarify our understanding by focusing on three specific technologies that use differenttype of algorithms in the security and surveillance industry: image processing, video analytics andartificial intelligence.
• This report is one of a series focusing on Artificial Intelligence computing. Datacenters, automotiveand consumer segments have been covered already and are updated regularly.
• To contribute to the understanding of the impact of software in the semiconductor industry bytaking a look at what is happening on the semiconductor side and computing hardware inparticular: CPU, GPU, FPGA and ASIC for AI.
• To establish the state-of-the-art processing and computing hardware required to accomplish simpleto heavy tasks such as running complex algorithms and, in particular, deep neural network inferencealgorithms.
• To provide an understanding of the ecosystem and technologies that depend on the specificverticals: smart home, smart retail, smart city and industry 4.0 .
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WHY THIS REPORT?
66
NEW MARKETS
Where everything is smart.
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Smart city
Smart retail
Smart home
Smart industry
Professional
surveillance
Consumer
surveillance
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WHERE TO FIND SURVEILLANCE? BECOMING A SMARTER WORLD
More cameras means more processing and computing hardware
Infrastructure
Transportation
City surveillance
Public places
Commercial
Industrial and defense
Enterprises & data centers
Banking & financial buildings
Hospitality centers
Retail stores & malls
Warehouses
Industry automation
Prison & correctional facilities
Border surveillance
Coastal surveillance
Public facility
Healthcare buildings
Educational buildings
Government buildings
Religious buildings
Consumer
Indoor
Outdoor
Doorbells
88
Provide a scenario for computing within the dynamics of the surveillance market, and present an understandingofAI’s impact on the semiconductor industry:
o Hardware - revenue forecast, volume shipments forecast
o Systems - ASP forecast, revenue forecast, volume shipments forecast
o Focus on artificial intelligence
Deliver an in-depth understanding of the ecosystem & players:
o Who are the players? What are the relationships inside this ecosystem?
o Who are the key suppliers to watch, and what technologies do they provide?
Offer key technical insights and analyses into future technology trends and challenges:
o Key technology choices
o Technology dynamics
o Emerging technologies and roadmaps
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REPORT OBJECTIVES
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METHODOLOGIES & DEFINITIONS
Market
Volume (in Munits)
ASP (in $)
Revenue (in $M)
Yole’s market forecast model is based on the matching of several sources:
Information
Aggregation
Preexisting
information
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METHODOLOGY
From world demography to processing hardware
Volume of cameras in worldwide cities
Global volume of cameras
Revenue generated
Volume of cameras in China
FOCUS
Consolidation with surveillance
companies’ revenues
Global volume of processing and
computing hardware
Revenue generated
Wafer starts
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WHO SHOULD BE INTERESTED IN THIS REPORT?
IC manufacturers and vendors, IP sellers:
o Evaluate the market potential of future technologiesand products for new applicative markets
o Screen potential new suppliers introducing newdisruptive technologies
o Monitor and benchmark your competitors’advancements
Surveillance, sensor and AI-related companies:
o Spot new technologies and define diversificationstrategies
o Position your company in the ecosystem
Technology suppliers:
o Understand the strategies of both the big players andstart-ups
Equipment and materials manufacturers:
o Understand ecosystem dynamics
o Realize the differentiated value of your products andtechnologies in this market
o Identify new business opportunities and prospects
Tier 1s and OEMs:
o Analyze the benefits of using these new technologies inyour end-system
o Filter and select new suppliers
Financial and strategic investors:
o Understand the potential of technologies and markets
o Acquaint yourself with key emerging companies andstart-ups
1212
• The National Information Security Standardization TechnicalCommittee, which is subordinate to the China CommunicationsStandards Association, has, as of 27 November 2019, started aproject to create a standard for facial recognition in China. Theproject is led by SenseTime and has been assigned to a workinggroup comprising 27 Chinese companies. As of 27 November2019, it is not known whether the created standards will bebinding.
• By 2020, the Chinese government expects to integrate privateand public cameras, leveraging the country's technologicalexpertise in facial recognition technology to build a nation-widesurveillance network.
• The government is promoting the development of artificialintelligence (AI) enabled cameras to prevent the spread ofCOVID-19 with the help of leading Chinese technologicalcompanies such as Hikvision, Dahua, iFlyTek, SenseTime, and Jiadu.Cameras are equipped with AI-enabled body temperaturedetection technology to prevent infected people from traveling.
• Moreover, the government is promoting a mobile applicationnamed “Health Code” that assigns a QR code along with a colorranking: green (the person is free to travel), yellow or red (theperson must be quarantined). The application has become anintegral part of Chinese authorities’ ability to manage a person’smovements in and out of affected areas. It uses city surveillancesystems to detect the person’s past and present location andsurroundings to determine whether they were near infectedpersons.
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INFRASTRUCTURE AND PUBLIC FACILITY SURVEILLANCE
China already implements Artificial Intelligence for biometric identification
AI means deployment of vision processors
that can handle these algorithms
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COMMERCIAL SURVEILLANCE
Applications
Advanced cameras provide people counting functionality which
counts foot traffic at store entrances and can export
daily/monthly/yearly reports. Traffic analyses greatly improve
business efficiency. People counting can be set to monitor
traffic flow in specific regions.
A fisheye camera provides heat map functionality displaying hot
and cold areas based on customer flow, allowing for enhanced
business analysis. Fisheye cameras also provide a 360-degree
image of the store floor.
HD and PTZ cameras in parking lots automatically and instantly
track and respond to abnormal behavior. When situations such
as accidents or burglaries arise, HD video provides detailed
evidence to confirm facts and alert authorities timeously.
These applications mean deployment of powerful ISPs and
vision processors that can handle the algorithms
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ON THE ROAD TO AN AUGMENTED INTELLIGENCE IN CONSUMER APPLICATIONS
RobotSmart AugmentationPC Mobile
ImagingCamera
Smart speaker
Smart camera
Wearables
Companion robotOlfactometry
Smart nose
Motion sensing
Holographic interaction
Augmented human
Robot home
PC
Audio
Mobile
Speaker
Smart hearables
Smart assistantSmartwatch
Smart TV
Smartwatch
SMARTPHONE
+ Accelerator + NeuromorphicApplication processorStandalone CPU, GPU,
memory and connectivity
SMARTPHONE
SMARTPHONE
>20302000 2010 2020
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INDUSTRY AND DEFENSE
Industry 4.0
• Enhanced video surveillance technologies promise torevolutionize the efficiency and effectiveness ofmanufacturing environments.
• These solutions combine cutting-edge video cameras,storage and management hardware together with modernmachine learning and analytics technology to provide theability to automatically analyze, detect and trigger alerts onevents seen by cameras in real time.
• Common use cases involve traditional physical securityapplications, worker safety and operational management:
o Detect motion in a restricted area
o Monitor the movement of valuable assets
o Distinguish unknown faces on a factory floor from employeesand partners identified through facial recognition technology
o Read license plates to identify the vehicles entering and leaving afacility
o Detect and count the number of people or vehicles in an area
o Inspect raw materials and finished goods
Analytic capabilities, which are a must, have to be more
competitive and may be found across a variety of
components. Some features may be built into cameras and
other sensors deployed on the edge/fog. However, because of
bandwidth issues and latency constraints, the trend is clearly to
embed processing and computing within the camera
1616
HOW DOES IT WORK?
Digital/IP camera infrastructure
Processing is done inside the cameras and computing in the NVR.
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Router/Firewall
ModemInternet
Remote PC
Other devices
Power
Coax
Ethernet / Optic
Power over ethernet
(POE) switch
Network Video Recorder (NVR)
Local PC
Processing
ComputingMonitor
Digital
Computing
Analysis
1717
FROM GENERAL APPLICATIONS TO NEURAL NETWORKS
Parallelization is key to explain why GPUs are so popular.
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Source: Deep Learning: An Artificial Intelligence Revolution
by ARK Investment
from
General ApplicationsGeneral workloads• Integer operations
• Tend to be sequential in nature
CPUsFew powerful cores that tackle
computing tasks sequentially
Only allocates a few transistors to
floating point operations
to
Neural NetworksDeep learning workloads• Floating operations
• Tend to be parallel in nature
GPUsHundreds of specialized cores
working in parallel
Most transistors are devoted to
floating point operations
Shift of the performance focus for the semiconductor industry
18
Scalar Processing
• Processes a single operation per instruction
• CPUs run at clock speeds in the GHz range
• May take a long time to execute large matrix operations via a
sequence of scalar operations
GOING FURTHER WITH DEDICATED AI UNITS
From GPUs to accelerators
Graph processing at the heart of neural networks.
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Vector Processing
• Same operation performed concurrently across a large number of
data elements at the same time
• GPUs are effectively vector processors
Graph Processing
• Runs many computational processes (vertices)
• Calculates the effects of these vertices on other points with which they
interact via lines (i.e. edges)
• Overall processing works on many vertices and points simultaneously
• Low precision needed
• Names : accelerators, neural engine, tensor processing unit
(TPU), neural network processor (NNP), intelligence processing unit
(IPU), vision processing unit (VPU) and graphic processing unit (GPU)
ASIC
1919
Source: FCC ID
VISION PROCESSOR ON THE MARKET TODAY
A vision processor – Ambarella S2L series
Ambarella S2LSystem-on-chip solution that integrates an
advanced image sensor pipeline (ISP), an H.264
encoder capable of up to 5Mp30 video, and a
powerful ARM® Cortex™-A9 CPU for user
applications.
AXIS M1065-L Network Camera
Retail
Ring Doorbell Pro
Consumer
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Characteristic Value
Packaging size
Packaging type
121mm²
BGA
Die size 18mm²
Node 28nm
Estimated ASP $7
2020
2020
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FORECASTS CAMERAS
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TECHNOLOGICAL SEGMENTATION OF HARDWARE FOR SURVEILLANCEIMAGE SIGNAL PROCESSOR IMAGE SIGNAL PROCESSOR
+ VISION PROCESSOR
IMAGE SIGNAL PROCESSOR
+ VISION PROCESSOR
+ ACCELERATOR
Standalone chip Standalone System-on-Chip
Standalone System-on-Chip
or
System-on-Chip + coprocessor
$3 to $5 $5 to $8 $8 to $25
Image processing pipeline
+ video codecDetection Recognition
Processing Video analytics Artificial Intelligence
Hi3516EV300
Vision ProcessorOmniVision ISP
Ambarella CV22 Vision
Processor
Performance
Application
Price
Domain
Architecture
Entry level
Video processor
Mid-level
Video processorHigh-end
Video processor
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FORECASTS PROCESSING AND COMPUTING IC
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PROCESSING AND COMPUTING FOR SURVEILLANCE ECOSYSTEM
Description
ProcessingVery fragmented
ecosystem with a lot
of small players in
China. Very difficult for
them to get into
computing (AI) as it
needs specific
architecture and
lowest nodes.
Computing2 main players:
Ambarella and
HiSilicon that share
almost all the
market.
SensingSome players
provide their own
processing solution
to gain some added
value from their
image sensors.
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ECOSYSTEMS, SUPPLY CHAINS AND ROADMAPS
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THE VALUE CHAIN FOLLOWS THE DATA FLOW
SenseSensor $0.1 - $1
ProcessHardware $1-$8 Human
99%
ComputeHardware $10-$100
IPLicense/Royalties
AnalyzeHardware >$1000
The output of the Process
step is of the same type as
the input. Processing value
is measured through how
the Compute step is
facilitated
On top of the image/sound,
information is provided. The
quality and precision of this
information as a function of the
computing power defines the
value of the Compute step
Maximum level of value is reached here, the Analyze step, with
dedicated information that is used for understanding habits and
center of interests, and for training to get better algorithms for
behavioral analysis and biometry and fill databases
Steal the car
99%
26
Contact our
Sales Team
for more
information
Artificial Intelligence Computing for Automotive
2020
Artificial Intelligence Computing for Consumer 2019
(x)PU: High-End CPU and GPU for Datacenter Applications
2020
CMOS Image Sensor Quarterly Market Monitor
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YOLE GROUP OF COMPANIES RELATED REPORTS
Yole Développement
27
Contact our
Sales Team
for more
information
Teardown Tracks
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YOLE GROUP OF COMPANIES RELATED REPORTS
System Plus Consulting
28About Yole Développement | www.yole.fr | ©2020
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