Insights on the Face Recognition Edge Computing Global Market to 2026 - Featuring Alphabet, Apple and Mediatek Among Others

Dublin, Jan. 04, 2022 (GLOBE NEWSWIRE) -- The "Face Recognition using Edge Computing Market Research Report by Device Type, Component, Application, and Region - Global Forecast to 2026 - Cumulative Impact of COVID-19" report has been added to's offering.

The Global Face Recognition using Edge Computing Market size was estimated at USD 937.84 million in 2020, is expected to reach USD 1,125.58 million in 2021, and projected to grow at a CAGR of 20.35% reaching USD 2,850.79 million by 2026.

Market Statistics

The report provides market sizing and forecast across five major currencies - USD, EUR GBP, JPY, and AUD. It helps organization leaders make better decisions when currency exchange data is readily available. In this report, the years 2018 and 2019 are considered historical years, 2020 as the base year, 2021 as the estimated year, and years from 2022 to 2026 are considered the forecast period.

Market Segmentation & Coverage

This research report categorizes the Face Recognition using Edge Computing to forecast the revenues and analyze the trends in each of the following sub-markets:

  • Based on Device Type, the market was studied across Integrated and Standalone.
  • Based on Component, the market was studied across Hardware, Services, and Software.
  • Based on Application, the market was studied across Access Control, Advertising, Attendance Tracking & Monitoring, eLearning, Emotion Recognition, Law Enforcement, Payment, and Robotics.
  • Based on Region, the market was studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, and Thailand. The Europe, Middle East & Africa is further studied across France, Germany, Italy, Netherlands, Qatar, Russia, Saudi Arabia, South Africa, Spain, United Arab Emirates, and United Kingdom.

Competitive Strategic Window

The Competitive Strategic Window analyses the competitive landscape in terms of markets, applications, and geographies to help the vendor define an alignment or fit between their capabilities and opportunities for future growth prospects. It describes the optimal or favorable fit for the vendors to adopt successive merger and acquisition strategies, geography expansion, research & development, and new product introduction strategies to execute further business expansion and growth during a forecast period.

FPNV Positioning Matrix

The FPNV Positioning Matrix evaluates and categorizes the vendors in the Face Recognition using Edge Computing Market based on Business Strategy (Business Growth, Industry Coverage, Financial Viability, and Channel Support) and Product Satisfaction (Value for Money, Ease of Use, Product Features, and Customer Support) that aids businesses in better decision making and understanding the competitive landscape.

Market Share Analysis

The Market Share Analysis offers the analysis of vendors considering their contribution to the overall market. It provides the idea of its revenue generation into the overall market compared to other vendors in the space. It provides insights into how vendors are performing in terms of revenue generation and customer base compared to others. Knowing market share offers an idea of the size and competitiveness of the vendors for the base year. It reveals the market characteristics in terms of accumulation, fragmentation, dominance, and amalgamation traits.

Company Usability Profiles

The report profoundly explores the recent significant developments by the leading vendors and innovation profiles in the Global Face Recognition using Edge Computing Market, including Alphabet, Inc., Apple, Inc., Applied Brain Research, Arm Holdings, Cadence Design Systems, Inc., Horizon Robotics, Huawei Technologies Co., Ltd., IDEMIA, Mediatek, Inc., Micron Technology, Microsoft Corporation, NVIDIA Corporation, Qualcomm Incorporated, Samsung Electronics, and Xilinx, Inc.

The report provides insights on the following pointers:
1. Market Penetration: Provides comprehensive information on the market offered by the key players
2. Market Development: Provides in-depth information about lucrative emerging markets and analyze penetration across mature segments of the markets
3. Market Diversification: Provides detailed information about new product launches, untapped geographies, recent developments, and investments
4. Competitive Assessment & Intelligence: Provides an exhaustive assessment of market shares, strategies, products, certification, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players
5. Product Development & Innovation: Provides intelligent insights on future technologies, R&D activities, and breakthrough product developments

The report answers questions such as:
1. What is the market size and forecast of the Global Face Recognition using Edge Computing Market?
2. What are the inhibiting factors and impact of COVID-19 shaping the Global Face Recognition using Edge Computing Market during the forecast period?
3. Which are the products/segments/applications/areas to invest in over the forecast period in the Global Face Recognition using Edge Computing Market?
4. What is the competitive strategic window for opportunities in the Global Face Recognition using Edge Computing Market?
5. What are the technology trends and regulatory frameworks in the Global Face Recognition using Edge Computing Market?
6. What is the market share of the leading vendors in the Global Face Recognition using Edge Computing Market?
7. What modes and strategic moves are considered suitable for entering the Global Face Recognition using Edge Computing Market?

Key Topics Covered:

1. Preface

2. Research Methodology

3. Executive Summary

4. Market Overview
4.1. Introduction
4.2. Cumulative Impact of COVID-19

5. Market Dynamics
5.1. Introduction
5.2. Drivers
5.2.1. Increasing adoption of facial recognition using edge computing
5.2.2. Growing adoption to resolve latency-specific issues in face recognition applications
5.2.3. Succoring real-time and intelligent applications
5.3. Restraints
5.3.1. Issues over security and user mobility
5.4. Opportunities
5.4.1. Seamless and personalized experience to improve business processes
5.4.2. Increasing integration with AI drones and video surveillance
5.5. Challenges
5.5.1. Technical and computational issues with embedded device such as interoperability, accessibility, and configuration

6. Face Recognition using Edge Computing Market, by Device Type
6.1. Introduction
6.2. Integrated
6.3. Standalone

7. Face Recognition using Edge Computing Market, by Component
7.1. Introduction
7.2. Hardware
7.3. Services
7.4. Software

8. Face Recognition using Edge Computing Market, by Application
8.1. Introduction
8.2. Access Control
8.3. Advertising
8.4. Attendance Tracking & Monitoring
8.5. eLearning
8.6. Emotion Recognition
8.7. Law Enforcement
8.8. Payment
8.9. Robotics

9. Americas Face Recognition using Edge Computing Market
9.1. Introduction
9.2. Argentina
9.3. Brazil
9.4. Canada
9.5. Mexico
9.6. United States

10. Asia-Pacific Face Recognition using Edge Computing Market
10.1. Introduction
10.2. Australia
10.3. China
10.4. India
10.5. Indonesia
10.6. Japan
10.7. Malaysia
10.8. Philippines
10.9. Singapore
10.10. South Korea
10.11. Taiwan
10.12. Thailand

11. Europe, Middle East & Africa Face Recognition using Edge Computing Market
11.1. Introduction
11.2. France
11.3. Germany
11.4. Italy
11.5. Netherlands
11.6. Qatar
11.7. Russia
11.8. Saudi Arabia
11.9. South Africa
11.10. Spain
11.11. United Arab Emirates
11.12. United Kingdom

12. Competitive Landscape
12.1. FPNV Positioning Matrix
12.1.1. Quadrants
12.1.2. Business Strategy
12.1.3. Product Satisfaction
12.2. Market Ranking Analysis
12.3. Market Share Analysis, by Key Player
12.4. Competitive Scenario
12.4.1. Merger & Acquisition
12.4.2. Agreement, Collaboration, & Partnership
12.4.3. New Product Launch & Enhancement
12.4.4. Investment & Funding
12.4.5. Award, Recognition, & Expansion

13. Company Usability Profiles
13.1. Alphabet, Inc.
13.2. Apple, Inc.
13.3. Applied Brain Research
13.4. Arm Holdings
13.5. Cadence Design Systems, Inc.
13.6. Horizon Robotics
13.7. Huawei Technologies Co., Ltd.
13.8. IDEMIA
13.9. Mediatek, Inc.
13.10. Micron Technology
13.11. Microsoft Corporation
13.12. NVIDIA Corporation
13.13. Qualcomm Incorporated
13.14. Samsung Electronics
13.15. Xilinx, Inc.

14. Appendix

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