Global machine-to-machine connections sales revenue in 2022 totaled US$ 25.8 billion. Overall demand for machine-to-machine connections will rise at 6.3% CAGR from 2022 to 2032. By 2032, the global machine-to-machine connections market size will reach US$ 47.5 billion.
Most of the demand for machine-to-machine (M2M) connections will arise from automotive & transportation sector. The target segment is set to progress at over 5.8% CAGR from 2022 to 2032, thereby making it a key-revenue generation segment for manufacturers.
Technology or connections that allow for direct communication between two machines or devices without human intervention are known as machine-to-machine connections.
M2M connections allow two devices to communicate autonomously using any communication channel, including wireless and wired. Sensors, Wi-Fi-, cellular communications, RFID, and software are key components of machine-to-machine systems.
Machine-to-machine technology allows devices on a network to make autonomous decisions without manual actions. M2M connections are widely used in manufacturing sector. Hence, expansion of the manufacturing industry and adoption of automation or factor automation will boost machine-to-machine demand.
Rising usage of M2M connections in applications such as healthcare, automotive, and the internet of things (IoT) will fuel sales. M2M connections help end users reduce costs, increase revenue, and improve customer service.
Today, sectors such as oil & gas, military, public utilities, manufacturing, precision agriculture, smart cities, etc. use machine-to-machine technologies for a wide variety of applications.
Companies are realizing the value of connecting dispersed people, sensors, devices, and machines to corporate networks. As a result, the worldwide machine-to-machine industry is set to witness a positive growth trajectory.
M2M connections, unlike supervisory control and data acquisition (SCADA), use public networks such as ethernet and cellular. Hence, they are cost-effective which makes them highly popular.
Growing applications of M2M connections in smart home systems and remote healthcare monitoring will also stimulate market development.
In telemedicine, M2M connections employ sensors to monitor a patient’s vital information. This critical information can then be transferred over to a doctor or a local machine that dispatches medicines.
Widening usage of M2M communication systems in predictive maintenance, supply chain management, and smart asset tracking will create new growth prospects.
Regionally, Asia Pacific will continue to remain at the epicenter of M2M connections market. Asia Pacific machine-to-machine connections market value reached US$ 13.1 billion in 2022. By 2032, Asia Pacific market value will total US$ 24.1 billion.
Asia Pacific is emerging as a leading market for IoT in the world. With the rapid adoption of IoT devices in the region, demand for M2M connections is projected to increase at a significant pace.
M2M connections can help to reduce human involvement in the decision-making process. They improve efficiency and reduce errors in data processing. Hence, they are gaining wider popularity in IoT or connected devices.
| Attributes | Key Insights |
|---|---|
| Machine-to-Machine Connections Market Size in (2022) | US$ 25.8 billion |
| Projected Machine-to-Machine Connections Market Value (2032) | US$ 47.5 billion |
| Machine-to-Machine Connections Market CAGR (2022 to 2032) | 6.3% |
| USA Market CAGR (2022 to 2032) | 5.1% |
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Historically, from 2017 to 2021, the value of the M2M connections market increased at 4.2% CAGR. Total market value at the end of 2021 reached around US$ 24.8 billion. Between 2022 and 2032, Future Market Insights predicts global machine-to-machine connections demand to rise at 6.3% CAGR.
Machine-to-machine (M2M) connections refer to the direct communication between two or more machines or devices without any human intervention.
M2M connections enable devices to exchange data and information in real time. They can be used in a variety of applications and industries, including healthcare, transportation, logistics, manufacturing, and energy.
M2M connections can improve efficiency, reduce costs, and enable new business models by automating processes, increasing visibility and control over operations. They can also provide real-time data and analytics.
With increasing adoption of Internet of Things (IoT) technology, M2M connections are becoming more prevalent. They are likely to play a critical role in the development of smart cities, smart factories, and other IoT applications.
M2M connections enable various devices, sensors, and machines to interact with each other and exchange information, which can be used to make automated decisions or trigger actions in IoT applications.
The key advantage of implementing M2M connections in IoT is that they can help to reduce human involvement in the decision-making process, thereby improving efficiency and reducing errors. This can be particularly valuable in industrial settings, where machines and sensors can work together to optimize production processes and minimize downtime.
The implementation of IoT is expanding throughout the world with around 7 billion IoT devices currently operating in the world. The number of IoT devices is projected to increase to around 25.4 billion devices. With increasing number of IoT devices, demand for M2M connections will rise at a robust pace.
Overall, M2M connections are a crucial aspect of the IoT ecosystem. They enable devices and machines to interact with each other and exchange data in a seamless and automated manner, leading to improved efficiency and productivity.
The demand for connected devices is increasing rapidly across industries, including healthcare, transportation, logistics, and manufacturing. Therefore, there is a rise in the adoption of M2M connections, as these devices require seamless communication and data transfer between machines.
Cloud computing is also becoming increasingly popular, as it provides a scalable and cost-effective way to store and process large amounts of data. M2M connections can leverage cloud computing to store and analyze data generated by connected devices, which is driving the adoption of M2M connections.
Increasing adoption of M2M in cloud computing will boost machine-to-machine connection sales revenue. This is because M2M connections enable efficient communication in cloud computing, thereby allowing devices to communicate with each other and with cloud services in real time.
M2M connections also allow for fast and efficient data processing and decision-making. Driven by this, demand for machine-to-machine connections will increase at a healthy pace through 2032.
Principal Consultant
| Country | United States |
|---|---|
| Projected CAGR (2022 to 2032) | 5.1% |
| Historical CAGR (2017 to 2021) | 1.3% |
| Market Value (2032) | US$ 6.8 billion |
| Country | United Kingdom |
|---|---|
| Projected CAGR (2022 to 2032) | 4.7% |
| Historical CAGR (2017 to 2021) | 0.4% |
| Market Value (2032) | US$ 1.2 billion |
| Country | China |
|---|---|
| Projected CAGR (2022 to 2032) | 7.7% |
| Historical CAGR (2017 to 2021) | 6.3% |
| Market Value (2032) | US$ 12.6 billion |
| Country | Japan |
|---|---|
| Projected CAGR (2022 to 2032) | 6.5% |
| Historical CAGR (2017 to 2021) | 5.3% |
| Market Value (2032) | US$ 8.5 billion |
| Country | South Korea |
|---|---|
| Projected CAGR (2022 to 2032) | 6.7% |
| Historical CAGR (2017 to 2021) | 5.6% |
| Market Value (2032) | US$ 3.0 billion |
Rising Adoption of IoT Devices Elevating Machine-to-Machine Demand in the United States
The United States machine-to-machine connections market expanded at 1.3% CAGR from 2017 to 2021. Overall machine-to-machine sales revenue in the USA will surge at 5.1% CAGR through 2032.
By the end of 2032, the United States machine-to-machine connections industry is set to cross a valuation of US$ 6.8 billion. It will create an absolute $ opportunity of US$ 2.7 billion over the next decade.
Rising penetration of IoT devices across the United States will drive the M2M connections market during the projection period.
The United States had around 3.9 billion IoT devices in 2020 which is projected to increase to around 7.6 billion IoT devices by the year 2025.
With increasing adoption of IoT in the country, demand for M2M connections is projected to increase at a steady pace. This is because they enhance efficiency and reduce errors in data processing.
Increasing popularity of smart grids and smart meters along with high adoption in remote patients monitoring systems will boost sales in the United States.
Growing IoT Usage Across Automotive and Consumer Sectors to Bolster M2M Applications in China
Machine-to-machine connection demand in China is set to rise at 7.7% CAGR through 2032 in comparison to 6.3% CAGR registered from 2017 to 2021. Total market valuation in China will reach around US$ 12.6 billion by 2032.
Increasing popularity of IoT devices along with rapid expansion of industries such as automotive, consumer electronics, utilities, etc. is driving China market.
China is a predominant country in the adoption of IoT in the world with around 3.3 billion IoT devices in the year 2020. By 2032, total number of IoT devices in China is projected to increase to around 8.5 billion.
With the increase in the adoption of IoT devices, demand for M2M connections will rise at a healthy pace.
Wireless Technologies Gaining Huge Traction
Based on technology, the M2M connections market is divided into wired technologies and wireless technologies. Among these, wireless technologies are gaining huge traction and the trend is likely to continue through 2032.
From 2017 to 2021, the wireless technologies segment expanded at 4.1% CAGR. Over the next ten years, the wireless technology used in machine-to-machine connections will rise at 6.0% CAGR.
Today, end users are shifting their preference towards wireless technologies. This is due to various advantages that wireless technologies offer.
Automotive & Transportation Sector Will Remain the Leading Consumer
As per Future Market Insights (FMI), automotive & transportation sector will continue to dominate the global market. This is due to rising applications of M2M connections in thriving automotive sector.
Demand for M2M connections from automotive and transportation sector grew at 4.0% CAGR between 2017 and 2021. Over the next decade, the target segment will thrive at a CAGR of 5.8%.
Machine-to-machine (M2M) connections are increasingly being used in the automotive and transportation industry to improve safety, efficiency, and customer experience.
M2M connections can be used in fleet management applications to monitor and track vehicles in real-time. This can help optimize routes, reduce fuel consumption, and improve driver safety.
Telematics systems use M2M connections to collect and transmit data from vehicles, including location, speed, fuel consumption, and engine performance. This data can be used for insurance purposes, to optimize maintenance schedules, and to improve driver behavior.
M2M connections can be used in ITS applications to improve traffic flow, reduce congestion, and enhance safety. For example, M2M connections can enable real-time traffic monitoring and management, adaptive traffic signal control, and automated tolling.
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Key companies in the market are investing heavily in research and development for introducing new and efficient solutions. The companies are also utilizing strategies such as acquisitions, partnerships, alliances, mergers, and collaborations to expand their presence.
Leading players in the market include Vodafone Group PLC, AT&T Inc., Texas Instruments Incorporated, Commsolid GmbH., Huawei Technologies Co., Ltd., Murata Manufacturing Co., U-Blox Holding AG, NXP Semiconductors N.V., Cisco Systems Inc., Intel Corporation, Fanstel Corporation, and Thales, Ltd.
Recent developments
| Attribute | Details |
|---|---|
| Estimated Market Size (2022) | US$ 25.8 billion |
| Projected Market Value (2032) | US$ 47.5 billion |
| Anticipated Growth Rate (2022 to 2032) | 6.3% CAGR |
| Forecast Period | 2022 to 2032 |
| Historical Data Available for | 2017 to 2021 |
| Industry Analysis | US$ Million for Value and Kilo Tons for Volume |
| Key Countries Covered | Germany, Italy, France, United Kingdom, Spain, BENELUX, Poland, Hungary, Romania, Czech Republic, Bosnia and Herzegovina, Bulgaria, Croatia, Rest of Europe |
| Key Segments Covered | Technology, End User, and Region |
| Key Companies Profiled | AT&T Inc.; Cisco Systems Inc.; Huawei Technologies Co.Ltd.; NXP Semiconductors N.V.; Texas Instruments Incorporated; Intel Corporation; Thales; Vodafone Group PLC; Murata Manufacturing Co., Ltd.; U-Blox Holding AG; Fanstel Corporation; Commsolid GmbH |
| Report Coverage | Market Forecast, Company Share Analysis, Competition Intelligence, DROT Analysis, Market Dynamics and Challenges, and Strategic Growth Initiatives |
The market is expected to advance at a CAGR of 6.3% through 2033.
The market in United States is expected to expand at a CAGR of 5.1% through 2033.
China is expected to offer monumental growth to market players.
Surging trend of smart cities and connected cars are expected to fuel market growth.
Wireless technologies are gaining higher popularity.
1. Executive Summary | Machine-to-Machine Connections Market
1.1. Global Market Outlook
1.2. Demand-side Trends
1.3. Supply-side Trends
1.4. Technology Roadmap Analysis
1.5. Analysis and Recommendations
2. Market Overview
2.1. Market Coverage / Taxonomy
2.2. Market Definition / Scope / Limitations
3. Market Background
3.1. Market Dynamics
3.1.1. Drivers
3.1.2. Restraints
3.1.3. Opportunity
3.1.4. Trends
3.2. Scenario Forecast
3.2.1. Demand in Optimistic Scenario
3.2.2. Demand in Likely Scenario
3.2.3. Demand in Conservative Scenario
3.3. Opportunity Map Analysis
3.4. Investment Feasibility Matrix
3.5. PESTLE and Porter’s Analysis
3.6. Regulatory Landscape
3.6.1. By Key Regions
3.6.2. By Key Countries
3.7. Regional Parent Market Outlook
4. Global Market Analysis 2017 to 2021 and Forecast, 2022 to 2032
4.1. Historical Market Size Value (US$ million) Analysis, 2017 to 2021
4.2. Current and Future Market Size Value (US$ million) Projections, 2022 to 2032
4.2.1. Y-o-Y Growth Trend Analysis
4.2.2. Absolute $ Opportunity Analysis
5. Global Market Analysis 2017 to 2021 and Forecast 2022 to 2032, By Technology
5.1. Introduction / Key Findings
5.2. Historical Market Size Value (US$ million) Analysis By Technology, 2017 to 2021
5.3. Current and Future Market Size Value (US$ million) Analysis and Forecast By Technology, 2022 to 2032
5.3.1. Wired Technologies
5.3.1.1. Ethernet
5.3.1.2. Industrial
5.3.2. Wireless Technologies
5.3.2.1. Short Range
5.3.2.2. Cellular Network
5.4. Y-o-Y Growth Trend Analysis By Technology, 2017 to 2021
5.5. Absolute $ Opportunity Analysis By Technology, 2022 to 2032
6. Global Market Analysis 2017 to 2021 and Forecast 2022 to 2032, By End User
6.1. Introduction / Key Findings
6.2. Historical Market Size Value (US$ million) Analysis By End User, 2017 to 2021
6.3. Current and Future Market Size Value (US$ million) Analysis and Forecast By End User, 2022 to 2032
6.3.1. Healthcare
6.3.1.1. Patient Monitoring Systems
6.3.1.2. Fall Detector
6.3.1.3. Smart Pill Dispenser
6.3.1.4. Telemedicine
6.3.2. Utilities
6.3.2.1. Smart Grids
6.3.2.2. Smart Meters
6.3.3. Automotive and Transportation
6.3.3.1. Telematics
6.3.3.2. Fleet Tracking/Monitoring
6.3.4. Retail
6.3.4.1. Intelligent Vending Machines
6.3.4.2. Contactless Checkout/Pos
6.3.4.3. Digital Signage
6.3.5. Consumer Electronics
6.3.5.1. Smart TV
6.3.5.2. Smart Appliances
6.3.6. Security & Surveillance
6.3.6.1. Commercial & Residential Security
6.3.6.2. Remote Surveillance
6.3.7. Others
6.3.7.1. Oil & Gas
6.3.7.2. Agriculture
6.4. Y-o-Y Growth Trend Analysis By End User, 2017 to 2021
6.5. Absolute $ Opportunity Analysis By End User, 2022 to 2032
7. Global Market Analysis 2017 to 2021 and Forecast 2022 to 2032, By Region
7.1. Introduction
7.2. Historical Market Size Value (US$ million) Analysis By Region, 2017 to 2021
7.3. Current Market Size Value (US$ million) Analysis and Forecast By Region, 2022 to 2032
7.3.1. North America
7.3.2. Latin America
7.3.3. Europe
7.3.4. Asia Pacific
7.3.5. Middle East & Africa
7.4. Market Attractiveness Analysis By Region
8. North America Market Analysis 2017 to 2021 and Forecast 2022 to 2032, By Country
8.1. Historical Market Size Value (US$ million) Trend Analysis By Market Taxonomy, 2017 to 2021
8.2. Market Size Value (US$ million) Forecast By Market Taxonomy, 2022 to 2032
8.2.1. By Country
8.2.1.1. United States
8.2.1.2. Canada
8.2.2. By Technology
8.2.3. By End User
8.3. Market Attractiveness Analysis
8.3.1. By Country
8.3.2. By Technology
8.3.3. By End User
8.4. Key Takeaways
9. Latin America Market Analysis 2017 to 2021 and Forecast 2022 to 2032, By Country
9.1. Historical Market Size Value (US$ million) Trend Analysis By Market Taxonomy, 2017 to 2021
9.2. Market Size Value (US$ million) Forecast By Market Taxonomy, 2022 to 2032
9.2.1. By Country
9.2.1.1. Brazil
9.2.1.2. Mexico
9.2.1.3. Rest of Latin America
9.2.2. By Technology
9.2.3. By End User
9.3. Market Attractiveness Analysis
9.3.1. By Country
9.3.2. By Technology
9.3.3. By End User
9.4. Key Takeaways
10. Europe Market Analysis 2017 to 2021 and Forecast 2022 to 2032, By Country
10.1. Historical Market Size Value (US$ million) Trend Analysis By Market Taxonomy, 2017 to 2021
10.2. Market Size Value (US$ million) Forecast By Market Taxonomy, 2022 to 2032
10.2.1. By Country
10.2.1.1. Germany
10.2.1.2. United Kingdom
10.2.1.3. France
10.2.1.4. Spain
10.2.1.5. Italy
10.2.1.6. Rest of Europe
10.2.2. By Technology
10.2.3. By End User
10.3. Market Attractiveness Analysis
10.3.1. By Country
10.3.2. By Technology
10.3.3. By End User
10.4. Key Takeaways
11. Asia Pacific Market Analysis 2017 to 2021 and Forecast 2022 to 2032, By Country
11.1. Historical Market Size Value (US$ million) Trend Analysis By Market Taxonomy, 2017 to 2021
11.2. Market Size Value (US$ million) Forecast By Market Taxonomy, 2022 to 2032
11.2.1. By Country
11.2.1.1. China
11.2.1.2. Japan
11.2.1.3. South Korea
11.2.1.4. Singapore
11.2.1.5. Thailand
11.2.1.6. Indonesia
11.2.1.7. Australia
11.2.1.8. New Zealand
11.2.1.9. Rest of Asia Pacific
11.2.2. By Technology
11.2.3. By End User
11.3. Market Attractiveness Analysis
11.3.1. By Country
11.3.2. By Technology
11.3.3. By End User
11.4. Key Takeaways
12. Middle East & Africa Market Analysis 2017 to 2021 and Forecast 2022 to 2032, By Country
12.1. Historical Market Size Value (US$ million) Trend Analysis By Market Taxonomy, 2017 to 2021
12.2. Market Size Value (US$ million) Forecast By Market Taxonomy, 2022 to 2032
12.2.1. By Country
12.2.1.1. Gulf Cooperation Council Countries
12.2.1.2. South Africa
12.2.1.3. Israel
12.2.1.4. Rest of Middle East & Africa
12.2.2. By Technology
12.2.3. By End User
12.3. Market Attractiveness Analysis
12.3.1. By Country
12.3.2. By Technology
12.3.3. By End User
12.4. Key Takeaways
13. Key Countries Market Analysis
13.1. United States
13.1.1. Pricing Analysis
13.1.2. Market Share Analysis, 2022
13.1.2.1. By Technology
13.1.2.2. By End User
13.2. Canada
13.2.1. Pricing Analysis
13.2.2. Market Share Analysis, 2022
13.2.2.1. By Technology
13.2.2.2. By End User
13.3. Brazil
13.3.1. Pricing Analysis
13.3.2. Market Share Analysis, 2022
13.3.2.1. By Technology
13.3.2.2. By End User
13.4. Mexico
13.4.1. Pricing Analysis
13.4.2. Market Share Analysis, 2022
13.4.2.1. By Technology
13.4.2.2. By End User
13.5. Germany
13.5.1. Pricing Analysis
13.5.2. Market Share Analysis, 2022
13.5.2.1. By Technology
13.5.2.2. By End User
13.6. United Kingdom
13.6.1. Pricing Analysis
13.6.2. Market Share Analysis, 2022
13.6.2.1. By Technology
13.6.2.2. By End User
13.7. France
13.7.1. Pricing Analysis
13.7.2. Market Share Analysis, 2022
13.7.2.1. By Technology
13.7.2.2. By End User
13.8. Spain
13.8.1. Pricing Analysis
13.8.2. Market Share Analysis, 2022
13.8.2.1. By Technology
13.8.2.2. By End User
13.9. Italy
13.9.1. Pricing Analysis
13.9.2. Market Share Analysis, 2022
13.9.2.1. By Technology
13.9.2.2. By End User
13.10. China
13.10.1. Pricing Analysis
13.10.2. Market Share Analysis, 2022
13.10.2.1. By Technology
13.10.2.2. By End User
13.11. Japan
13.11.1. Pricing Analysis
13.11.2. Market Share Analysis, 2022
13.11.2.1. By Technology
13.11.2.2. By End User
13.12. South Korea
13.12.1. Pricing Analysis
13.12.2. Market Share Analysis, 2022
13.12.2.1. By Technology
13.12.2.2. By End User
13.13. Singapore
13.13.1. Pricing Analysis
13.13.2. Market Share Analysis, 2022
13.13.2.1. By Technology
13.13.2.2. By End User
13.14. Thailand
13.14.1. Pricing Analysis
13.14.2. Market Share Analysis, 2022
13.14.2.1. By Technology
13.14.2.2. By End User
13.15. Indonesia
13.15.1. Pricing Analysis
13.15.2. Market Share Analysis, 2022
13.15.2.1. By Technology
13.15.2.2. By End User
13.16. Australia
13.16.1. Pricing Analysis
13.16.2. Market Share Analysis, 2022
13.16.2.1. By Technology
13.16.2.2. By End User
13.17. New Zealand
13.17.1. Pricing Analysis
13.17.2. Market Share Analysis, 2022
13.17.2.1. By Technology
13.17.2.2. By End User
13.18. Gulf Cooperation Council Countries
13.18.1. Pricing Analysis
13.18.2. Market Share Analysis, 2022
13.18.2.1. By Technology
13.18.2.2. By End User
13.19. South Africa
13.19.1. Pricing Analysis
13.19.2. Market Share Analysis, 2022
13.19.2.1. By Technology
13.19.2.2. By End User
13.20. Israel
13.20.1. Pricing Analysis
13.20.2. Market Share Analysis, 2022
13.20.2.1. By Technology
13.20.2.2. By End User
14. Market Structure Analysis
14.1. Competition Dashboard
14.2. Competition Benchmarking
14.3. Market Share Analysis of Top Players
14.3.1. By Regional
14.3.2. By Technology
14.3.3. By End User
15. Competition Analysis
15.1. Competition Deep Dive
15.1.1. AT&T Inc.
15.1.1.1. Overview
15.1.1.2. Product Portfolio
15.1.1.3. Profitability by Market Segments
15.1.1.4. Sales Footprint
15.1.1.5. Strategy Overview
15.1.1.5.1. Marketing Strategy
15.1.2. Cisco Systems Inc.
15.1.2.1. Overview
15.1.2.2. Product Portfolio
15.1.2.3. Profitability by Market Segments
15.1.2.4. Sales Footprint
15.1.2.5. Strategy Overview
15.1.2.5.1. Marketing Strategy
15.1.3. Huawei Technologies Co., Ltd.
15.1.3.1. Overview
15.1.3.2. Product Portfolio
15.1.3.3. Profitability by Market Segments
15.1.3.4. Sales Footprint
15.1.3.5. Strategy Overview
15.1.3.5.1. Marketing Strategy
15.1.4. NXP Semiconductors N.V.
15.1.4.1. Overview
15.1.4.2. Product Portfolio
15.1.4.3. Profitability by Market Segments
15.1.4.4. Sales Footprint
15.1.4.5. Strategy Overview
15.1.4.5.1. Marketing Strategy
15.1.5. Texas Instruments Incorporated
15.1.5.1. Overview
15.1.5.2. Product Portfolio
15.1.5.3. Profitability by Market Segments
15.1.5.4. Sales Footprint
15.1.5.5. Strategy Overview
15.1.5.5.1. Marketing Strategy
15.1.6. Intel Corporation
15.1.6.1. Overview
15.1.6.2. Product Portfolio
15.1.6.3. Profitability by Market Segments
15.1.6.4. Sales Footprint
15.1.6.5. Strategy Overview
15.1.6.5.1. Marketing Strategy
15.1.7. Thales
15.1.7.1. Overview
15.1.7.2. Product Portfolio
15.1.7.3. Profitability by Market Segments
15.1.7.4. Sales Footprint
15.1.7.5. Strategy Overview
15.1.7.5.1. Marketing Strategy
15.1.8. Vodafone Group PLC
15.1.8.1. Overview
15.1.8.2. Product Portfolio
15.1.8.3. Profitability by Market Segments
15.1.8.4. Sales Footprint
15.1.8.5. Strategy Overview
15.1.8.5.1. Marketing Strategy
15.1.9. Murata Manufacturing Co., Ltd.
15.1.9.1. Overview
15.1.9.2. Product Portfolio
15.1.9.3. Profitability by Market Segments
15.1.9.4. Sales Footprint
15.1.9.5. Strategy Overview
15.1.9.5.1. Marketing Strategy
15.1.10. U-Blox Holding AG
15.1.10.1. Overview
15.1.10.2. Product Portfolio
15.1.10.3. Profitability by Market Segments
15.1.10.4. Sales Footprint
15.1.10.5. Strategy Overview
15.1.10.5.1. Marketing Strategy
15.1.11. Fanstel Corporation
15.1.11.1. Overview
15.1.11.2. Product Portfolio
15.1.11.3. Profitability by Market Segments
15.1.11.4. Sales Footprint
15.1.11.5. Strategy Overview
15.1.11.5.1. Marketing Strategy
15.1.12. Commsolid GmbH
15.1.12.1. Overview
15.1.12.2. Product Portfolio
15.1.12.3. Profitability by Market Segments
15.1.12.4. Sales Footprint
15.1.12.5. Strategy Overview
15.1.12.5.1. Marketing Strategy
16. Assumptions & Acronyms Used
17. Research Methodology
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Machine-to-Machine Connections Market
