Dublin, Jan. 21, 2022 (GLOBE NEWSWIRE) -- The "Global Face Recognition Using Edge Computing Market (2021-2026) by Components, Application, Device Type, End-User, and Geography, Competitive Analysis and the Impact of Covid-19 with Ansoff Analysis" report has been added to ResearchAndMarkets.com's offering.
The Global Face Recognition Using Edge Computing Market is estimated to be USD 1,136.9 Mn in 2021 and is expected to reach USD 2,964.7 Mn by 2026, growing at a CAGR of 21.3%.
Market Dynamics
Key factors such as the rising need for adequate surveillance and safety of individuals with the increasing number of identity crises have led to a demand for a highly accurate facial recognition system. Automated identification has also led to the demand for these facial recognition systems in several sectors such as banking, healthcare, airlines. The growing usage of IoT has increased the volume of data. With edge computing, transmitting a massive volume of data to the cloud has lessened latency and real-time experience, increasing market demand. However, a potential breach of privacy is likely to restrain the market growth.
The Global Face Recognition Using Edge Computing Market is segmented based on Components, Application, Device Type, End-User, and Geography.
Company Profiles
Some of the companies covered in this report are Alphabet, Inc., Apple, Inc., Applied Brain Research, Arm Holdings, Cadence Design Systems, Inc., IDEMIA, Mediatek, Inc., Microsoft Corporation, NVIDIA Corporation, Qualcomm Incorporated, Samsung Electronics, and Xilinx, Inc.
Countries Studied
- America (Argentina, Brazil, Canada, Chile, Colombia, Mexico, Peru, United States, Rest of Americas)
- Europe (Austria, Belgium, Denmark, Finland, France, Germany, Italy, Netherlands, Norway, Poland, Russia, Spain, Sweden, Switzerland, United Kingdom, Rest of Europe)
- Middle-East and Africa (Egypt, Israel, Qatar, Saudi Arabia, South Africa, United Arab Emirates, Rest of MEA)
- Asia-Pacific (Australia, Bangladesh, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Sri Lanka, Thailand, Taiwan, Rest of Asia-Pacific)
Competitive Quadrant
The report includes a Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.
Why buy this report?
- The report offers a comprehensive evaluation of the Global Face Recognition Using Edge Computing Market. The report includes in-depth qualitative analysis, verifiable data from authentic sources, and projections about market size. The projections are calculated using proven research methodologies.
- The report has been compiled through extensive primary and secondary research. The primary research is done through interviews, surveys, and observation of renowned personnel in the industry.
- The report includes an in-depth market analysis using Porter's 5 forces model and the Ansoff Matrix. In addition, the impact of Covid-19 on the market is also featured in the report.
- The report also includes the regulatory scenario in the industry, which will help you make a well-informed decision. The report discusses major regulatory bodies and major rules and regulations imposed on this sector across various geographies.
- The report also contains the competitive analysis using Positioning Quadrants, the analyst's Proprietary competitive positioning tool.
Key Topics Covered:
1 Report Description
2 Research Methodology
3 Executive Summary
3.1 Introduction
3.2 Market Size and Segmentation
3.3 Market Outlook
4 Market Influencers
4.1 Drivers
4.1.1 Need for Adequate Security, Encryption & Privacy
4.1.2 Optimizing The Accuracy Levels of Facial Recognition Systems and Mask Detection
4.1.3 Rising Number of IoT Devices and Cloud-Based Applications
4.1.4 Growing Adoption to Resolve Latency-Specific Issues in Facial Recognition
4.2 Restraints
4.2.1 Security Concerns
4.3 Opportunities
4.3.1 Rising Demand in On-Premise Devices and Workstations
4.3.2 Integration of AI Chipset
4.4 Challenges
4.4.1 Technical and Computational Issues with an Embedded Device such as Interoperability, Accessibility, and Configuration
5 Market Analysis
5.1 Regulatory Scenario
5.2 Porter's Five Forces Analysis
5.3 Impact of COVID-19
5.4 Ansoff Matrix Analysis
1 Global Face Recognition Using Edge Computing Market, By Device Type
1.1 Introduction
1.2 Integrated
1.3 Standalone
2 Global Face Recognition Using Edge Computing Market, By Components
2.1 Introduction
2.2 Hardware
2.3 Software
2.4 Services
3 Global Face Recognition Using Edge Computing Market, By Application
3.1 Introduction
3.2 Access Control
3.3 Surveillance and Security
3.4 Authentication
3.5 Advertising
3.6 E-Learning
3.7 Emotion Recognition
3.8 Law Enforcement
3.9 Robotics
4 Global Face Recognition Using Edge Computing Market, By End User
4.1 Introduction
4.2 Hospitality
4.3 Banking and Finance
4.4 Retail
4.5 Government and Defense
4.6 Industrial Facilities
4.7 Others
6 Global Face Recognition Using Edge Computing Market, By Geography
7 Competitive Landscape
7.1 Competitive Quadrant
7.2 Market Share Analysis
7.3 Strategic Initiatives
7.3.1 M&A and Investments
7.3.2 Partnerships and Collaborations
7.3.3 Product Developments and Improvements
8 Company Profiles
8.1 Alphabet, Inc.
8.2 Apple, Inc.
8.3 Cadence Design Systems, Inc.
8.4 Beijing Horizon Robotics Technology Co., Ltd.
8.5 Huawei Technologies Co., Ltd.
8.6 IDEMIA
8.7 Mediatek, Inc.
8.8 Micron Technology Inc.
8.9 Microsoft Corporation
8.10 Nvidia Corporation
8.11 Qualcomm Incorporated
8.12 Samsung Electronics
8.13 Xilinx, Inc
8.14 Cisco Systems, Inc.
8.15 Belden Inc.
8.16 IBM Corporation
8.17 Intel Corporation
8.18 Moxa Inc.
8.19 Megvii
8.20 Clear Secure, Inc.
9 Appendix
For more information about this report visit https://www.researchandmarkets.com/r/ignsvq
