Highlights
The global Edge Machine Learning (Edge ML) market was valued at US$ million in 2022 and is anticipated to reach US$ million by 2029, witnessing a CAGR of % during the forecast period 2023-2029. The influence of COVID-19 and the Russia-Ukraine War were considered while estimating market sizes.
North American market for Edge Machine Learning (Edge ML) is estimated to increase from $ million in 2023 to reach $ million by 2029, at a CAGR of % during the forecast period of 2023 through 2029.
Asia-Pacific market for Edge Machine Learning (Edge ML) is estimated to increase from $ million in 2023 to reach $ million by 2029, at a CAGR of % during the forecast period of 2023 through 2029.
The global market for Edge Machine Learning (Edge ML) in Automotive is estimated to increase from $ million in 2023 to $ million by 2029, at a CAGR of % during the forecast period of 2023 through 2029.
The key global companies of Edge Machine Learning (Edge ML) include Microsoft, Edge Impulse, Imagimob, SensiML, Latent AI, Plumerai, DeGirum, NXP and Ekkono Solutions, etc. In 2022, the world's top three vendors accounted for approximately % of the revenue.
Report Scope
This report aims to provide a comprehensive presentation of the global market for Edge Machine Learning (Edge ML), with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Edge Machine Learning (Edge ML).
The Edge Machine Learning (Edge ML) market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2022 as the base year, with history and forecast data for the period from 2018 to 2029. This report segments the global Edge Machine Learning (Edge ML) market comprehensively. Regional market sizes, concerning products by type, by application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Edge Machine Learning (Edge ML) companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by type, by application, and by regions.
By Company
Microsoft
Edge Impulse
Imagimob
SensiML
Latent AI
Plumerai
DeGirum
NXP
Ekkono Solutions
Mj酶lner Informatics
STMicroelectronics
Segment by Type
Hardware
Software and Services
Segment by Application
Automotive
Manufacturing
Retail
Agriculture
Healthcare
Other
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Core Chapters
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by type, application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Edge Machine Learning (Edge ML) companies鈥� competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the key companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.
1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Edge Machine Learning (Edge ML) Market Size Growth Rate by Type: 2018 VS 2022 VS 2029
1.2.2 Hardware
1.2.3 Software and Services
1.3 Market by Application
1.3.1 Global Edge Machine Learning (Edge ML) Market Growth by Application: 2018 VS 2022 VS 2029
1.3.2 Automotive
1.3.3 Manufacturing
1.3.4 Retail
1.3.5 Agriculture
1.3.6 Healthcare
1.3.7 Other
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Edge Machine Learning (Edge ML) Market Perspective (2018-2029)
2.2 Edge Machine Learning (Edge ML) Growth Trends by Region
2.2.1 Global Edge Machine Learning (Edge ML) Market Size by Region: 2018 VS 2022 VS 2029
2.2.2 Edge Machine Learning (Edge ML) Historic Market Size by Region (2018-2023)
2.2.3 Edge Machine Learning (Edge ML) Forecasted Market Size by Region (2024-2029)
2.3 Edge Machine Learning (Edge ML) Market Dynamics
2.3.1 Edge Machine Learning (Edge ML) Industry Trends
2.3.2 Edge Machine Learning (Edge ML) Market Drivers
2.3.3 Edge Machine Learning (Edge ML) Market Challenges
2.3.4 Edge Machine Learning (Edge ML) Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Edge Machine Learning (Edge ML) Players by Revenue
3.1.1 Global Top Edge Machine Learning (Edge ML) Players by Revenue (2018-2023)
3.1.2 Global Edge Machine Learning (Edge ML) Revenue Market Share by Players (2018-2023)
3.2 Global Edge Machine Learning (Edge ML) Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Edge Machine Learning (Edge ML) Revenue
3.4 Global Edge Machine Learning (Edge ML) Market Concentration Ratio
3.4.1 Global Edge Machine Learning (Edge ML) Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Edge Machine Learning (Edge ML) Revenue in 2022
3.5 Edge Machine Learning (Edge ML) Key Players Head office and Area Served
3.6 Key Players Edge Machine Learning (Edge ML) Product Solution and Service
3.7 Date of Enter into Edge Machine Learning (Edge ML) Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Edge Machine Learning (Edge ML) Breakdown Data by Type
4.1 Global Edge Machine Learning (Edge ML) Historic Market Size by Type (2018-2023)
4.2 Global Edge Machine Learning (Edge ML) Forecasted Market Size by Type (2024-2029)
5 Edge Machine Learning (Edge ML) Breakdown Data by Application
5.1 Global Edge Machine Learning (Edge ML) Historic Market Size by Application (2018-2023)
5.2 Global Edge Machine Learning (Edge ML) Forecasted Market Size by Application (2024-2029)
6 North America
6.1 North America Edge Machine Learning (Edge ML) Market Size (2018-2029)
6.2 North America Edge Machine Learning (Edge ML) Market Growth Rate by Country: 2018 VS 2022 VS 2029
6.3 North America Edge Machine Learning (Edge ML) Market Size by Country (2018-2023)
6.4 North America Edge Machine Learning (Edge ML) Market Size by Country (2024-2029)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Edge Machine Learning (Edge ML) Market Size (2018-2029)
7.2 Europe Edge Machine Learning (Edge ML) Market Growth Rate by Country: 2018 VS 2022 VS 2029
7.3 Europe Edge Machine Learning (Edge ML) Market Size by Country (2018-2023)
7.4 Europe Edge Machine Learning (Edge ML) Market Size by Country (2024-2029)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Edge Machine Learning (Edge ML) Market Size (2018-2029)
8.2 Asia-Pacific Edge Machine Learning (Edge ML) Market Growth Rate by Region: 2018 VS 2022 VS 2029
8.3 Asia-Pacific Edge Machine Learning (Edge ML) Market Size by Region (2018-2023)
8.4 Asia-Pacific Edge Machine Learning (Edge ML) Market Size by Region (2024-2029)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Edge Machine Learning (Edge ML) Market Size (2018-2029)
9.2 Latin America Edge Machine Learning (Edge ML) Market Growth Rate by Country: 2018 VS 2022 VS 2029
9.3 Latin America Edge Machine Learning (Edge ML) Market Size by Country (2018-2023)
9.4 Latin America Edge Machine Learning (Edge ML) Market Size by Country (2024-2029)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Edge Machine Learning (Edge ML) Market Size (2018-2029)
10.2 Middle East & Africa Edge Machine Learning (Edge ML) Market Growth Rate by Country: 2018 VS 2022 VS 2029
10.3 Middle East & Africa Edge Machine Learning (Edge ML) Market Size by Country (2018-2023)
10.4 Middle East & Africa Edge Machine Learning (Edge ML) Market Size by Country (2024-2029)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Microsoft
11.1.1 Microsoft Company Detail
11.1.2 Microsoft Business Overview
11.1.3 Microsoft Edge Machine Learning (Edge ML) Introduction
11.1.4 Microsoft Revenue in Edge Machine Learning (Edge ML) Business (2018-2023)
11.1.5 Microsoft Recent Development
11.2 Edge Impulse
11.2.1 Edge Impulse Company Detail
11.2.2 Edge Impulse Business Overview
11.2.3 Edge Impulse Edge Machine Learning (Edge ML) Introduction
11.2.4 Edge Impulse Revenue in Edge Machine Learning (Edge ML) Business (2018-2023)
11.2.5 Edge Impulse Recent Development
11.3 Imagimob
11.3.1 Imagimob Company Detail
11.3.2 Imagimob Business Overview
11.3.3 Imagimob Edge Machine Learning (Edge ML) Introduction
11.3.4 Imagimob Revenue in Edge Machine Learning (Edge ML) Business (2018-2023)
11.3.5 Imagimob Recent Development
11.4 SensiML
11.4.1 SensiML Company Detail
11.4.2 SensiML Business Overview
11.4.3 SensiML Edge Machine Learning (Edge ML) Introduction
11.4.4 SensiML Revenue in Edge Machine Learning (Edge ML) Business (2018-2023)
11.4.5 SensiML Recent Development
11.5 Latent AI
11.5.1 Latent AI Company Detail
11.5.2 Latent AI Business Overview
11.5.3 Latent AI Edge Machine Learning (Edge ML) Introduction
11.5.4 Latent AI Revenue in Edge Machine Learning (Edge ML) Business (2018-2023)
11.5.5 Latent AI Recent Development
11.6 Plumerai
11.6.1 Plumerai Company Detail
11.6.2 Plumerai Business Overview
11.6.3 Plumerai Edge Machine Learning (Edge ML) Introduction
11.6.4 Plumerai Revenue in Edge Machine Learning (Edge ML) Business (2018-2023)
11.6.5 Plumerai Recent Development
11.7 DeGirum
11.7.1 DeGirum Company Detail
11.7.2 DeGirum Business Overview
11.7.3 DeGirum Edge Machine Learning (Edge ML) Introduction
11.7.4 DeGirum Revenue in Edge Machine Learning (Edge ML) Business (2018-2023)
11.7.5 DeGirum Recent Development
11.8 NXP
11.8.1 NXP Company Detail
11.8.2 NXP Business Overview
11.8.3 NXP Edge Machine Learning (Edge ML) Introduction
11.8.4 NXP Revenue in Edge Machine Learning (Edge ML) Business (2018-2023)
11.8.5 NXP Recent Development
11.9 Ekkono Solutions
11.9.1 Ekkono Solutions Company Detail
11.9.2 Ekkono Solutions Business Overview
11.9.3 Ekkono Solutions Edge Machine Learning (Edge ML) Introduction
11.9.4 Ekkono Solutions Revenue in Edge Machine Learning (Edge ML) Business (2018-2023)
11.9.5 Ekkono Solutions Recent Development
11.10 Mj酶lner Informatics
11.10.1 Mj酶lner Informatics Company Detail
11.10.2 Mj酶lner Informatics Business Overview
11.10.3 Mj酶lner Informatics Edge Machine Learning (Edge ML) Introduction
11.10.4 Mj酶lner Informatics Revenue in Edge Machine Learning (Edge ML) Business (2018-2023)
11.10.5 Mj酶lner Informatics Recent Development
11.11 STMicroelectronics
11.11.1 STMicroelectronics Company Detail
11.11.2 STMicroelectronics Business Overview
11.11.3 STMicroelectronics Edge Machine Learning (Edge ML) Introduction
11.11.4 STMicroelectronics Revenue in Edge Machine Learning (Edge ML) Business (2018-2023)
11.11.5 STMicroelectronics Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details
Microsoft
Edge Impulse
Imagimob
SensiML
Latent AI
Plumerai
DeGirum
NXP
Ekkono Solutions
Mj酶lner Informatics
STMicroelectronics
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*If Applicable.
