[PDF] Machine to Machine (M2M) Connections Market : Very Simple Things You Can Do To Grow

What Is Machine to Machine (M2M) Connections?

Machine to machine connections are usually used in warehouse management, supply chain management, and remote monitoring. For instance, machine to machine connections enables a retailing machine to directly communicate with the distributor regarding any particular product stock whenever it is running low by sending him a message. Hence, it is very important for warehouse and retail sector. Moreover, it and be utilized for traffic control, telemedicine, and fleet management.

Machine to Machine (M2M) Connections Market Key Players:

AT&T Inc., Cisco Systems Inc., Texas Instruments Incorporated, Huawei Technologies Co., Ltd., NXP Semiconductors N.V., Intel Corporation, Murata Manufacturing Co., Ltd., Gemalto N.V., Vodafone Group PLC, U-Blox Holding AG, Commsolid GmbH, and Fanstel Corporation.

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Machine to machine connections are usually used in warehouse management, supply chain management, and remote monitoring. For instance, machine to machine connections enables a retailing machine to directly communicate with the distributor regarding any particular product stock whenever it is running low by sending him a message. Hence, it is very important for warehouse and retail sector. Moreover, it and be utilized for traffic control, telemedicine, and fleet management.

Machine to Machine (M2M) Connections Market Taxonomy

On the basis of technology, the global machine to machine connection market is segmented into:

Wireless Technology
Cellular Network
4G/LTE
3G
2G
Short Range Network
Wi-Fi
Bluetooth
Zigbee
Wired Technology
Ethernet
Industrial
On the basis of end user industry, the global machine to machine connection market is segmented into:

Healthcare
Automotive & Transportation
Consumer Electronics
Utilities
Retail
Security & Surveillance
Others
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Preliminary Data Mining

The raw data is obtained through the secondary findings, in house repositories, and trade surveys. It is then filtered to ensure that the relevant information including industry dynamics, trends, and outlook is retained for further research process.

Data Standardization

Holistic approach is used to ensure that the granular and uncommon parameters are taken into consideration to ensure accurate results. The information from the paid databases are further combined to the raw data in order to standardize it.

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This release was published on openPR.