The AI in Edge Computing Market is expected to grow from USD 590 million in 2020 to USD 1,835 million by 2026 at a CAGR of 20.8% from 2020 to 2026.
Edge AI is a system which processes data generated at the local level by hardware devices using machine learning techniques. It refers to AI algorithms which are put forward locally on hardware devices and use data produced locally. They save the results locally on the devices before forwarding them to the cloud to be processed and stored. One of the major benefits of AI in edge computing is its speed. Integrating smart devices and functionality can detect faults and provide AI at the edge for insights. There is a wide range of AI in edge computing applications which majorly propels the market growth such as facial recognition and real-time traffic reports on smartphones and semi-autonomous vehicles or intelligent devices. Video games, security cameras, robots, smart speakers, drones and wearable health monitoring devices are among the other edge computing AI-enabled devices. The security camera detection procedure will benefit from edge computing AI. Conventional surveillance cameras take images for hours before storing and using them as required. With the edge AI, however, the algorithmic procedures will be performed in real-time in the system itself, enabling the cameras to identify and process suspicious activity in real-time, leading to more efficient and cost-effective services. The ability of autonomous vehicles to process data and images in real-time to detect traffic signs, pedestrians, other cars and roads will increase through Edge AI, improving transportation security. In respect of industrial IoT, Edge AI will decrease costs and increase safety (IIoT). Machine Learning will recompile data in real-time of the complete process, while AI will observe machinery for probable defects or faults in the production chain. However, the privacy and security issues associated to edge AI solutions to restrain the market.
Furthermore, the emergence of the 5G network is combing IT and telecommunications together and creating new possibilities for high-end applications to further minimize the network latency. The 5G network allow developing data centers at edge modules, as well as implementing industry-specific networks supported by virtualization and software-defined networking principles in a single environment. Vital AI applications, such as autonomous vehicles, surgery, industry automation and robotics, demand for ultra-low latency that is less than a round trip delay of 1 millisecond. These low latency rates can be attained by installing new hardware in air interfaces and adoption of edge nodes. The dawn of 5G networks among various applications is projected to increase the volume of data transferred to the data centers, thereby increasing the requirement for intermediary servers or edge networks.
The global AI in Edge Computing Market is segregated on the basis of Offering as Hardware, Solutions and Services. Based on End-User the global AI in Edge Computing Market is segmented in Manufacturing, Healthcare, Transportation, Government, Media and Entertainment, Energy and Utilities, Telecom and IT, Retail and Others.
The global AI in Edge Computing Market report provides geographic analysis covering regions, such as Europe, North America, Asia Pacific, and Rest of The World. The AI in Edge Computing Market for each region is further segmented for major countries including the U.S., Canada, Germany, the U.K., France, Italy, China, India, Japan, Brazil, South Africa, and others.
Competitive Analysis
Cisco Systems, Inc., ClearBlade, Inc., FogHorn Systems, Hewlett Packard Enterprise and others are among the major players in the global AI in Edge Computing Market. The companies studied in terms of product strategy and various n several growth and expansion strategies to gain a competitive edge in the market. The major players not only follow value chain integration with business operations in multiple stages of the value chain.
The global AI in Edge Computing Market has been segmented as below:
AI in Edge Computing Market, By Offering
AI in Edge Computing Market, By End-User
AI in Edge Computing Market, By Company
The report covers the below scope:
The years considered for the study are as follows:
Report Scope:
The global AI in Edge Computing Market report scope includes detailed study covering underlying factors influencing the industry trends. The report covers analysis on regional and country level market dynamics. The scope also covers competitive overview providing company market shares along with company profiles for major revenue contributing companies. The report scope includes detailed competitive outlook covering market shares and profiles key participants in the global AI in Edge Computing Market share. Major industry players with significant revenue share Cisco Systems, Inc., ClearBlade, Inc., FogHorn Systems, Hewlett Packard Enterprise and others.
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Report Content
1. Introduction
1.1. Key Points
1.2. Report Description
1.3. Markets Covered
1.4. Stakeholders
2. Research Methodology
2.1. Research Scope
2.2. Research Methodology
2.2.1. Market Research Process
2.2.2. Research Methodology
2.2.2.1. Secondary Research
2.2.2.2. Primary Research
2.2.2.3. Models for Estimation
2.3. Market Size Estimation
2.3.1. Bottom-Up Approach
2.3.2. Top-Down Approach
3. Executive Summary
4. Market Overview
4.1. Introduction
4.2. Drivers
4.3. Restraints
4.4. Opportunities
4.5. Challenges
5. AI in Edge Computing Market, By Offering
5.1. Key Points
5.2. Hardware
5.3. Solutions
5.4. Services
6. AI in Edge Computing Market, By End-User
6.1. Key Points
6.2. Manufacturing
6.3. Healthcare
6.4. Transportation
6.5. Government
6.6. Media and Entertainment
6.7. Energy and Utilities
6.8. Telecom and IT
6.9. Retail
6.10. Others
7. Competitive Landscape
7.1. Introduction
7.2. Start-up companies- AI in Edge Computing Market
7.3. Recent Developments
7.3.1. Mergers & Acquisitions
7.3.2. New Product Developments
7.3.3. Portfolio/Production Capacity Expansions
7.3.4. Joint Ventures, Collaborations, Partnerships & Agreements
7.3.5. Others
8. Company Profile
8.1. Cisco Systems, Inc.
8.2. ClearBlade, Inc.
8.3. FogHorn Systems
8.4. Hewlett Packard Enterprise
8.5. Huawei Technologies Co. Ltd.
8.6. IBM Corporation
8.7. Nokia Networks
8.8. Rigado, LLC
8.9. Saguna Networks Ltd.
8.10. Vapor IO
AI in Edge Computing Market, By Offering
AI in Edge Computing Market, By End-User