Tiny Machine Learning (TinyML) is a field of study in Machine Learning and Embedded Systems that explores the types of models you can run on small, low-powered devices like microcontrollers.
The global market for Tiny Machine Learning (TinyML) was estimated to be worth US$ 1025 million in 2023 and is forecast to a readjusted size of US$ 3478.4 million by 2030 with a CAGR of 9.8% during the forecast period 2024-2030
The market size has grown at a moderate pace over the past few years with a high growth rate, and the market is expected to grow significantly over the forecast period.
Report Scope
This report aims to provide a comprehensive presentation of the global market for Tiny Machine Learning (TinyML), focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Tiny Machine Learning (TinyML) by region & country, by Type, and by Application.
The Tiny Machine Learning (TinyML) market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. 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 Tiny Machine Learning (TinyML).
麻豆原创 Segmentation
By Company
Google
Microsoft
ARM
STMicroelectronics
Cartesian
Meta Platforms/Facebook
EdgeImpulse Inc.
Segment by Type:
C Language
Java
Segment by Application
Manufacturing
Retail
Agriculture
Healthcare
By Region
North America
U.S.
Canada
Europe
Germany
France
U.K.
Italy
Russia
Asia-Pacific
China
Japan
South Korea
China Taiwan
Southeast Asia
India
Latin America
Mexico
Brazil
Argentina
Middle East & Africa
Turkey
Saudi Arabia
U.A.E
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Tiny Machine Learning (TinyML) manufacturers competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: 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 4: 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 5: Revenue of Tiny Machine Learning (TinyML) in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of Tiny Machine Learning (TinyML) in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.
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1 麻豆原创 Overview
1.1 Tiny Machine Learning (TinyML) Product Introduction
1.2 Global Tiny Machine Learning (TinyML) 麻豆原创 Size Forecast
1.3 Tiny Machine Learning (TinyML) 麻豆原创 Trends & Drivers
1.3.1 Tiny Machine Learning (TinyML) Industry Trends
1.3.2 Tiny Machine Learning (TinyML) 麻豆原创 Drivers & Opportunity
1.3.3 Tiny Machine Learning (TinyML) 麻豆原创 Challenges
1.3.4 Tiny Machine Learning (TinyML) 麻豆原创 Restraints
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Competitive Analysis by Company
2.1 Global Tiny Machine Learning (TinyML) Players Revenue Ranking (2023)
2.2 Global Tiny Machine Learning (TinyML) Revenue by Company (2019-2024)
2.3 Key Companies Tiny Machine Learning (TinyML) Manufacturing Base Distribution and Headquarters
2.4 Key Companies Tiny Machine Learning (TinyML) Product Offered
2.5 Key Companies Time to Begin Mass Production of Tiny Machine Learning (TinyML)
2.6 Tiny Machine Learning (TinyML) 麻豆原创 Competitive Analysis
2.6.1 Tiny Machine Learning (TinyML) 麻豆原创 Concentration Rate (2019-2024)
2.6.2 Global 5 and 10 Largest Companies by Tiny Machine Learning (TinyML) Revenue in 2023
2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Tiny Machine Learning (TinyML) as of 2023)
2.7 Mergers & Acquisitions, Expansion
3 Segmentation by Type
3.1 Introduction by Type
3.1.1 C Language
3.1.2 Java
3.2 Global Tiny Machine Learning (TinyML) Sales Value by Type
3.2.1 Global Tiny Machine Learning (TinyML) Sales Value by Type (2019 VS 2023 VS 2030)
3.2.2 Global Tiny Machine Learning (TinyML) Sales Value, by Type (2019-2030)
3.2.3 Global Tiny Machine Learning (TinyML) Sales Value, by Type (%) (2019-2030)
4 Segmentation by Application
4.1 Introduction by Application
4.1.1 Manufacturing
4.1.2 Retail
4.1.3 Agriculture
4.1.4 Healthcare
4.2 Global Tiny Machine Learning (TinyML) Sales Value by Application
4.2.1 Global Tiny Machine Learning (TinyML) Sales Value by Application (2019 VS 2023 VS 2030)
4.2.2 Global Tiny Machine Learning (TinyML) Sales Value, by Application (2019-2030)
4.2.3 Global Tiny Machine Learning (TinyML) Sales Value, by Application (%) (2019-2030)
5 Segmentation by Region
5.1 Global Tiny Machine Learning (TinyML) Sales Value by Region
5.1.1 Global Tiny Machine Learning (TinyML) Sales Value by Region: 2019 VS 2023 VS 2030
5.1.2 Global Tiny Machine Learning (TinyML) Sales Value by Region (2019-2024)
5.1.3 Global Tiny Machine Learning (TinyML) Sales Value by Region (2025-2030)
5.1.4 Global Tiny Machine Learning (TinyML) Sales Value by Region (%), (2019-2030)
5.2 North America
5.2.1 North America Tiny Machine Learning (TinyML) Sales Value, 2019-2030
5.2.2 North America Tiny Machine Learning (TinyML) Sales Value by Country (%), 2023 VS 2030
5.3 Europe
5.3.1 Europe Tiny Machine Learning (TinyML) Sales Value, 2019-2030
5.3.2 Europe Tiny Machine Learning (TinyML) Sales Value by Country (%), 2023 VS 2030
5.4 Asia Pacific
5.4.1 Asia Pacific Tiny Machine Learning (TinyML) Sales Value, 2019-2030
5.4.2 Asia Pacific Tiny Machine Learning (TinyML) Sales Value by Country (%), 2023 VS 2030
5.5 South America
5.5.1 South America Tiny Machine Learning (TinyML) Sales Value, 2019-2030
5.5.2 South America Tiny Machine Learning (TinyML) Sales Value by Country (%), 2023 VS 2030
5.6 Middle East & Africa
5.6.1 Middle East & Africa Tiny Machine Learning (TinyML) Sales Value, 2019-2030
5.6.2 Middle East & Africa Tiny Machine Learning (TinyML) Sales Value by Country (%), 2023 VS 2030
6 Segmentation by Key Countries/Regions
6.1 Key Countries/Regions Tiny Machine Learning (TinyML) Sales Value Growth Trends, 2019 VS 2023 VS 2030
6.2 Key Countries/Regions Tiny Machine Learning (TinyML) Sales Value
6.3 United States
6.3.1 United States Tiny Machine Learning (TinyML) Sales Value, 2019-2030
6.3.2 United States Tiny Machine Learning (TinyML) Sales Value by Type (%), 2023 VS 2030
6.3.3 United States Tiny Machine Learning (TinyML) Sales Value by Application, 2023 VS 2030
6.4 Europe
6.4.1 Europe Tiny Machine Learning (TinyML) Sales Value, 2019-2030
6.4.2 Europe Tiny Machine Learning (TinyML) Sales Value by Type (%), 2023 VS 2030
6.4.3 Europe Tiny Machine Learning (TinyML) Sales Value by Application, 2023 VS 2030
6.5 China
6.5.1 China Tiny Machine Learning (TinyML) Sales Value, 2019-2030
6.5.2 China Tiny Machine Learning (TinyML) Sales Value by Type (%), 2023 VS 2030
6.5.3 China Tiny Machine Learning (TinyML) Sales Value by Application, 2023 VS 2030
6.6 Japan
6.6.1 Japan Tiny Machine Learning (TinyML) Sales Value, 2019-2030
6.6.2 Japan Tiny Machine Learning (TinyML) Sales Value by Type (%), 2023 VS 2030
6.6.3 Japan Tiny Machine Learning (TinyML) Sales Value by Application, 2023 VS 2030
6.7 South Korea
6.7.1 South Korea Tiny Machine Learning (TinyML) Sales Value, 2019-2030
6.7.2 South Korea Tiny Machine Learning (TinyML) Sales Value by Type (%), 2023 VS 2030
6.7.3 South Korea Tiny Machine Learning (TinyML) Sales Value by Application, 2023 VS 2030
6.8 Southeast Asia
6.8.1 Southeast Asia Tiny Machine Learning (TinyML) Sales Value, 2019-2030
6.8.2 Southeast Asia Tiny Machine Learning (TinyML) Sales Value by Type (%), 2023 VS 2030
6.8.3 Southeast Asia Tiny Machine Learning (TinyML) Sales Value by Application, 2023 VS 2030
6.9 India
6.9.1 India Tiny Machine Learning (TinyML) Sales Value, 2019-2030
6.9.2 India Tiny Machine Learning (TinyML) Sales Value by Type (%), 2023 VS 2030
6.9.3 India Tiny Machine Learning (TinyML) Sales Value by Application, 2023 VS 2030
7 Company Profiles
7.1 Google
7.1.1 Google Profile
7.1.2 Google Main Business
7.1.3 Google Tiny Machine Learning (TinyML) Products, Services and Solutions
7.1.4 Google Tiny Machine Learning (TinyML) Revenue (US$ Million) & (2019-2024)
7.1.5 Google Recent Developments
7.2 Microsoft
7.2.1 Microsoft Profile
7.2.2 Microsoft Main Business
7.2.3 Microsoft Tiny Machine Learning (TinyML) Products, Services and Solutions
7.2.4 Microsoft Tiny Machine Learning (TinyML) Revenue (US$ Million) & (2019-2024)
7.2.5 Microsoft Recent Developments
7.3 ARM
7.3.1 ARM Profile
7.3.2 ARM Main Business
7.3.3 ARM Tiny Machine Learning (TinyML) Products, Services and Solutions
7.3.4 ARM Tiny Machine Learning (TinyML) Revenue (US$ Million) & (2019-2024)
7.3.5 STMicroelectronics Recent Developments
7.4 STMicroelectronics
7.4.1 STMicroelectronics Profile
7.4.2 STMicroelectronics Main Business
7.4.3 STMicroelectronics Tiny Machine Learning (TinyML) Products, Services and Solutions
7.4.4 STMicroelectronics Tiny Machine Learning (TinyML) Revenue (US$ Million) & (2019-2024)
7.4.5 STMicroelectronics Recent Developments
7.5 Cartesian
7.5.1 Cartesian Profile
7.5.2 Cartesian Main Business
7.5.3 Cartesian Tiny Machine Learning (TinyML) Products, Services and Solutions
7.5.4 Cartesian Tiny Machine Learning (TinyML) Revenue (US$ Million) & (2019-2024)
7.5.5 Cartesian Recent Developments
7.6 Meta Platforms/Facebook
7.6.1 Meta Platforms/Facebook Profile
7.6.2 Meta Platforms/Facebook Main Business
7.6.3 Meta Platforms/Facebook Tiny Machine Learning (TinyML) Products, Services and Solutions
7.6.4 Meta Platforms/Facebook Tiny Machine Learning (TinyML) Revenue (US$ Million) & (2019-2024)
7.6.5 Meta Platforms/Facebook Recent Developments
7.7 EdgeImpulse Inc.
7.7.1 EdgeImpulse Inc. Profile
7.7.2 EdgeImpulse Inc. Main Business
7.7.3 EdgeImpulse Inc. Tiny Machine Learning (TinyML) Products, Services and Solutions
7.7.4 EdgeImpulse Inc. Tiny Machine Learning (TinyML) Revenue (US$ Million) & (2019-2024)
7.7.5 EdgeImpulse Inc. Recent Developments
8 Industry Chain Analysis
8.1 Tiny Machine Learning (TinyML) Industrial Chain
8.2 Tiny Machine Learning (TinyML) Upstream Analysis
8.2.1 Key Raw Materials
8.2.2 Raw Materials Key Suppliers
8.2.3 Manufacturing Cost Structure
8.3 Midstream Analysis
8.4 Downstream Analysis (Customers Analysis)
8.5 Sales Model and Sales Channels
8.5.1 Tiny Machine Learning (TinyML) Sales Model
8.5.2 Sales Channel
8.5.3 Tiny Machine Learning (TinyML) Distributors
9 Research Findings and Conclusion
10 Appendix
10.1 Research Methodology
10.1.1 Methodology/Research Approach
10.1.2 Data Source
10.2 Author Details
10.3 Disclaimer
Google
Microsoft
ARM
STMicroelectronics
Cartesian
Meta Platforms/Facebook
EdgeImpulse Inc.
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*If Applicable.
