세계의 엣지 컴퓨팅을 이용한 얼굴 인식 시장 : 컴포넌트, 디바이스 유형, 용도별 예측(2025-2030년)

The Face Recognition using Edge Computing Market was valued at USD 1.62 billion in 2023, expected to reach USD 1.96 billion in 2024, and is projected to grow at a CAGR of 20.55%, to USD 6.02 billion by 2030.

Face recognition using edge computing merges two cutting-edge technologies to deliver real-time data processing and analysis directly where data is generated, enhancing speed and security. This integration's necessity arises from the increasing demand for rapid, efficient, and secure processing of facial recognition tasks on devices like cameras and smartphones. Its applications are widespread, spanning across security and surveillance, retail analytics, healthcare, and personalized services. End-users primarily include sectors like law enforcement, enterprise security, and consumer electronics. The market is influenced by factors such as technological advancements, rising security concerns, and the proliferation of IoT devices. A significant growth driver is the demand for real-time processing, which minimizes latency and enhances decision-making. Opportunities abound in developing regions where infrastructure for centralized data processing lags, making edge solutions more viable. Furthermore, the increasing adoption of smart cities paves the way for innovative applications in traffic management and urban security. However, the market faces challenges such as data privacy concerns, high initial setup costs, and limited processing power of edge devices compared to cloud solutions. Regulatory hurdles concerning data use and protection also pose significant barriers. To capture emerging opportunities, businesses should focus on innovation in the development of efficient edge algorithms and inter-device communication protocols, ensuring robust cybersecurity measures to mitigate privacy concerns. Research could explore energy-efficient hardware and edge AI advancements, facilitating scalable deployments. With the market's dynamic nature underscored by rapid tech evolution and regulatory shifts, ongoing research and adaptation are essential. Companies must maintain strategic partnerships, invest in R&D, and remain agile in responses to market transitions, enabling them to leverage technological breakthroughs and adhere to emerging standards effectively.

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving Face Recognition using Edge Computing Market

The Face Recognition using Edge Computing Market is undergoing transformative changes driven by a dynamic interplay of supply and demand factors. Understanding these evolving market dynamics prepares business organizations to make informed investment decisions, refine strategic decisions, and seize new opportunities. By gaining a comprehensive view of these trends, business organizations can mitigate various risks across political, geographic, technical, social, and economic domains while also gaining a clearer understanding of consumer behavior and its impact on manufacturing costs and purchasing trends.

• Market Drivers
  • Increasing adoption of facial recognition using edge computing
  • Growing adoption to resolve latency-specific issues in face recognition applications
  • Succoring real-time and intelligent applications
• Market Restraints
  • Issues over security and user mobility
• Market Opportunities
  • Seamless and personalized experience to improve business processes
  • Increasing integration with AI drones and video surveillance
• Market Challenges
  • Technical and computational issues with embedded device

Porter's Five Forces: A Strategic Tool for Navigating the Face Recognition using Edge Computing Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the Face Recognition using Edge Computing Market. It offers business organizations with a clear methodology for evaluating their competitive positioning and exploring strategic opportunities. This framework helps businesses assess the power dynamics within the market and determine the profitability of new ventures. With these insights, business organizations can leverage their strengths, address weaknesses, and avoid potential challenges, ensuring a more resilient market positioning.

PESTLE Analysis: Navigating External Influences in the Face Recognition using Edge Computing Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the Face Recognition using Edge Computing Market. Political, Economic, Social, Technological, Legal, and Environmental factors analysis provides the necessary information to navigate these influences. By examining PESTLE factors, businesses can better understand potential risks and opportunities. This analysis enables business organizations to anticipate changes in regulations, consumer preferences, and economic trends, ensuring they are prepared to make proactive, forward-thinking decisions.

Market Share Analysis: Understanding the Competitive Landscape in the Face Recognition using Edge Computing Market

A detailed market share analysis in the Face Recognition using Edge Computing Market provides a comprehensive assessment of vendors' performance. Companies can identify their competitive positioning by comparing key metrics, including revenue, customer base, and growth rates. This analysis highlights market concentration, fragmentation, and trends in consolidation, offering vendors the insights required to make strategic decisions that enhance their position in an increasingly competitive landscape.

FPNV Positioning Matrix: Evaluating Vendors' Performance in the Face Recognition using Edge Computing Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the Face Recognition using Edge Computing Market. This matrix enables business organizations to make well-informed decisions that align with their goals by assessing vendors based on their business strategy and product satisfaction. The four quadrants provide a clear and precise segmentation of vendors, helping users identify the right partners and solutions that best fit their strategic objectives.

Strategy Analysis & Recommendation: Charting a Path to Success in the Face Recognition using Edge Computing Market

A strategic analysis of the Face Recognition using Edge Computing Market is essential for businesses looking to strengthen their global market presence. By reviewing key resources, capabilities, and performance indicators, business organizations can identify growth opportunities and work toward improvement. This approach helps businesses navigate challenges in the competitive landscape and ensures they are well-positioned to capitalize on newer opportunities and drive long-term success.

Key Company Profiles

The report delves into recent significant developments in the Face Recognition using Edge Computing Market, highlighting leading vendors and their innovative profiles. These include Alphabet, Inc., Arm Holdings, Cisco Systems, Inc., Clarifai, Inc., Huawei Technologies Co., Ltd., IDEMIA Group, IDEMIA NSS, LLC, Innovatrics, International Business Machines Corporation, Micron Technology, Inc., Microsoft Corporation, NEC Corporation by AT&T Inc., NVIDIA Corporation, Oosto by AnyVision Interactive Technologies Ltd., Qualcomm Incorporated, Samsung Electronics Co., Ltd., and Xailient Inc..

Market Segmentation & Coverage

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

• Based on Component, market is studied across Hardware, Services, and Software.
• Based on Device Type, market is studied across Integrated and Standalone.
• Based on Application, market is studied across Access Control, Advertising, Attendance Tracking & Monitoring, E-Learning, Emotion Recognition, Law Enforcement, Payment, and Robotics.
• Based on Region, market is 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, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

The report offers a comprehensive analysis of the market, covering key focus areas:

1. Market Penetration: A detailed review of the current market environment, including extensive data from top industry players, evaluating their market reach and overall influence.

2. Market Development: Identifies growth opportunities in emerging markets and assesses expansion potential in established sectors, providing a strategic roadmap for future growth.

3. Market Diversification: Analyzes recent product launches, untapped geographic regions, major industry advancements, and strategic investments reshaping the market.

4. Competitive Assessment & Intelligence: Provides a thorough analysis of the competitive landscape, examining market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, and technological advancements of key players.

5. Product Development & Innovation: Highlights cutting-edge technologies, R&D activities, and product innovations expected to drive future market growth.

The report also answers critical questions to aid stakeholders in making informed decisions:

1. What is the current market size, and what is the forecasted growth?

2. Which products, segments, and regions offer the best investment opportunities?

3. What are the key technology trends and regulatory influences shaping the market?

4. How do leading vendors rank in terms of market share and competitive positioning?

5. What revenue sources and strategic opportunities drive vendors' market entry or exit strategies?

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

• 2.1. Define: Research Objective
• 2.2. Determine: Research Design
• 2.3. Prepare: Research Instrument
• 2.4. Collect: Data Source
• 2.5. Analyze: Data Interpretation
• 2.6. Formulate: Data Verification
• 2.7. Publish: Research Report
• 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

• 5.1. Market Dynamics
  • 5.1.1. Drivers
    • 5.1.1.1. Increasing adoption of facial recognition using edge computing
    • 5.1.1.2. Growing adoption to resolve latency-specific issues in face recognition applications
    • 5.1.1.3. Succoring real-time and intelligent applications
  • 5.1.2. Restraints
    • 5.1.2.1. Issues over security and user mobility
  • 5.1.3. Opportunities
    • 5.1.3.1. Seamless and personalized experience to improve business processes
    • 5.1.3.2. Increasing integration with AI drones and video surveillance
  • 5.1.4. Challenges
    • 5.1.4.1. Technical and computational issues with embedded device
• 5.2. Market Segmentation Analysis
• 5.3. Porter's Five Forces Analysis
  • 5.3.1. Threat of New Entrants
  • 5.3.2. Threat of Substitutes
  • 5.3.3. Bargaining Power of Customers
  • 5.3.4. Bargaining Power of Suppliers
  • 5.3.5. Industry Rivalry
• 5.4. PESTLE Analysis
  • 5.4.1. Political
  • 5.4.2. Economic
  • 5.4.3. Social
  • 5.4.4. Technological
  • 5.4.5. Legal
  • 5.4.6. Environmental

6. Face Recognition using Edge Computing Market, by Component

• 6.1. Introduction
• 6.2. Hardware
• 6.3. Services
• 6.4. Software

7. Face Recognition using Edge Computing Market, by Device Type

• 7.1. Introduction
• 7.2. Integrated
• 7.3. Standalone

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. E-Learning
• 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
• 10.13. Vietnam

11. Europe, Middle East & Africa Face Recognition using Edge Computing Market

• 11.1. Introduction
• 11.2. Denmark
• 11.3. Egypt
• 11.4. Finland
• 11.5. France
• 11.6. Germany
• 11.7. Israel
• 11.8. Italy
• 11.9. Netherlands
• 11.10. Nigeria
• 11.11. Norway
• 11.12. Poland
• 11.13. Qatar
• 11.14. Russia
• 11.15. Saudi Arabia
• 11.16. South Africa
• 11.17. Spain
• 11.18. Sweden
• 11.19. Switzerland
• 11.20. Turkey
• 11.21. United Arab Emirates
• 11.22. United Kingdom

12. Competitive Landscape

• 12.1. Market Share Analysis, 2023
• 12.2. FPNV Positioning Matrix, 2023
• 12.3. Competitive Scenario Analysis
• 12.4. Strategy Analysis & Recommendation

Companies Mentioned

• 1. Alphabet, Inc.
• 2. Arm Holdings
• 3. Cisco Systems, Inc.
• 4. Clarifai, Inc.
• 5. Huawei Technologies Co., Ltd.
• 6. IDEMIA Group
• 7. IDEMIA NSS, LLC
• 8. Innovatrics
• 9. International Business Machines Corporation
• 10. Micron Technology, Inc.
• 11. Microsoft Corporation
• 12. NEC Corporation by AT&T Inc.
• 13. NVIDIA Corporation
• 14. Oosto by AnyVision Interactive Technologies Ltd.
• 15. Qualcomm Incorporated
• 16. Samsung Electronics Co., Ltd.
• 17. Xailient Inc.