Worldwide Face Recognition Using Edge Computing Industry to 2025 - Integration of Machine Learning and AI Presents Opportunities - ResearchAndMarkets.com

The "Global Face Recognition Using Edge Computing Market (2020-2025) by Components, Application, Device Type, End-User, 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 936.51 Mn in 2020 and is expected to reach USD 2.36 Bn by 2025, growing at a CAGR of 20.38%.

Market Segmentation

The Global Face Recognition Using Edge Computing Market is segmented further based on Components, Application, Device Type, End-User, and Geography.

By Components, the market is classified as Hardware, Services, and Software. Amongst the two, the software segment holds the highest market share.

By Application, the market is classified as access control, advertising, attendance tracking & monitoring, e-learning, emotion recognition, law enforcement, payment, and robotics. Amongst all, attendance tracking & monitoring holds the highest market share.

By Device Type, the market is classified as Integrated and Standalone. Amongst the two, the integrated segment holds the highest market share.

By Geography, North America is projected to lead the market.

Recent Developments

1. Qualcomm has bought another partner, PFU Limited, a Fujitsu Company to its Smart Cities Accelerator Program. The company shall be contributing to the development of facial biometric technologies and smart cameras on smart edge devices. -16th July 2020

2. Remark Holdings through its KanKan AI subsidiary has launched two new edge computing systems to perform facial recognition and other applications locally. These Smart Boxes are AI-powered edge computers and are equipped with NVIDIA's latest range of high-performance edge computing modules.- 11th December 2020

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 in-depth market analysis using Porter's 5 force model and the Ansoff Matrix. The impact of Covid-19 on the market is also featured in the report.
• The report also contains the competitive analysis using the Competitive Quadrant, the analyst's proprietary competitive positioning tool.

Report Highlights:

• A complete analysis of the market, including parent industry
• Important market dynamics and trends
• Market segmentation
• Historical, current, and projected size of the market based on value and volume
• Market shares and strategies of key players
• Recommendations to companies for strengthening their foothold in the market

Market Dynamics

Drivers

• Need for adequate surveillance and safety of individuals due to the rising identity crisis
• Optimizing the accuracy levels of facial recognition systems
• Increasing number of facial recognition systems in several industry sectors
• Growing adoption to resolve latency-specific issues in facial recognition

Restraints

• Security Concerns

Opportunities

• Increasing cloud-based applications
• Integration of machine learning and AI
• Rising number of IoT devices

Challenges

• Technical and computational issues with an embedded device such as interoperability, accessibility, and configuration

Companies Mentioned

• Alphabet, Inc.
• Apple, Inc.
• Applied Brain Research
• Arm Holdings (NVIDIA)
• Cadence Design Systems, Inc.
• Horizon Robotics
• Huawei Technologies Co., Ltd.
• IDEMIA
• Mediatek, Inc.
• Micron Technology
• Microsoft Corporation
• NVIDIA Corporation
• Qualcomm Incorporated
• Samsung Electronics
• Xilinx, Inc (AMD)
• Cisco Systems, Inc.
• Belden Inc.
• IBM Corporation
• Intel Corporation
• Moxa Inc.

For more information about this report visit https://www.researchandmarkets.com/r/c4axrj

View source version on businesswire.com: https://www.businesswire.com/news/home/20210722005495/en/