Difference Between IoT and M2M

Difference Between IoT and M2M

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Vikram Singh
Assistant Manager - Content
Updated on Jan 2, 2024 06:02 IST

It's important to distinguish between IoT (Internet of Things) and M2M (Machine to Machine) communication in today's rapidly evolving digital landscape. This article provides an in-depth analysis of the differences that set these technologies apart. We cover everything from their basic definitions to the complexities of their applications and scalability. You'll discover how IoT, which is broad and interconnected, differs significantly from M2M, which is more direct and task-focused.


The Internet of Things (IoT) is a system of interrelated intelligent devices, smart homes, and even smart cities. In the U.S. alone, nearly 70% of households own at least one smart device, and experts say the number of smart devices worldwide will more than double by 2027. This article defines M2M and IoT and examines their key differences. Understanding the difference between IoT and M2M will help you know which one is better suited for your business application.

Table of contents

What is the Difference Between IoT and M2M?

Parameter IoT (Internet of Things) M2M (Machine to Machine)
Definition IoT refers to a network of interconnected devices that can collect and exchange data using embedded sensors. M2M involves direct communication between devices using any means of communication, including wired and wireless.
Connectivity Typically uses the internet for connectivity. It can include a variety of protocols and standards like Wi-Fi, Bluetooth, 5G, and more. Primarily uses point-to-point communication through cellular or wired networks.
Scope Broad scope, involving various devices and applications, integrating data from different sources for comprehensive solutions. Narrower scope focused on specific tasks like data collection and control between one or more machines.
Interactivity High level of interactivity with devices, often communicating with multiple systems and platforms for integrated actions. Limited interactivity with usually one-way communication or simple two-way exchanges.
Data Handling Handles large volumes of data, often requiring sophisticated data analysis and processing capabilities. Typically involves the transfer of specific and often smaller datasets. Data processing is usually more straightforward.
Autonomy Devices in IoT can be more autonomous, making decisions and performing actions based on data analysis without human intervention. M2M devices generally perform predefined tasks and require more human intervention for complex decision-making.
Applications Wide-ranging applications, from smart homes to smart cities, healthcare, agriculture, and more. More focused on industrial and business applications like manufacturing, logistics, and utility management.
Complexity Generally more complex due to the integration of various devices, technologies, and platforms. Less complex as it involves direct communication between machines.
Interaction with Cloud Often relies on cloud computing for data analysis, storage, and additional processing. May not necessarily require cloud computing; focuses on direct communication between machines.
User Interface Typically includes a user interface for human interaction and monitoring, often accessible via smartphones or computers. User interface is not always a priority; the focus is more on machine interaction.
Scalability Highly scalable, capable of integrating an increasing number of devices and systems. Scalability is limited to the number of machines that can be interconnected directly or through a network.

IoT(Internet of things)

IoT is a network infrastructure that connects things to the Internet to send and receive data. IoT is a new concept where devices, applications, sensors, and actuators are connected through the Internet. For example, IoT networks connect things like street lights, parking meters, home appliances, and even clothing to the Internet. IoT allows these devices to communicate with each other and exchange data. These devices collect information from their surroundings and each other and send it to the network. You can access your data from various connected devices, such as mobile phones, laptops, cars, and even refrigerators.

Use cases of IoT

  • IoT for Asset/Plant Performance Optimization
  • IoT- based Quality Control & Management
  • On-Site Track and Trace
  • Location Tracking (e.g., GPS)
  • Remote Asset Monitoring and Control

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How does IoT work?

IoT devices share collected sensor data by connecting to IoT gateways or other edge devices. The data is either sent to the cloud for analysis or analyzed locally. These devices may communicate with other related devices and respond to information received from each other. The device does most of the work without human intervention, but humans can interact with the device, for example, for setup, instructions, and access to data.

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M2M(Machine to machine)

Machine-to-machine or M2M refers to direct communication between devices. Wired or wireless communication channels can be used without human intervention. This technology enables point-to-point communication between machines, sensors, and hardware. This allows the device to collect state information. You can send this information to other devices and use this information to control their behavior. The main goal is collecting data, sending it over the network, and taking action based on triggered events. M2M communication is favored by industries seeking more efficient, cheaper, and faster technology.

A typical example of machine-to-machine technology is controlling electrical devices such as fans and light bulbs via Bluetooth on smartphones. A smartphone and an electronic device are two interacting devices. Another example is the smart meter that can track electricity consumption in real time. M2M technology is widely used in applications such as track and trace, automation, metering, and healthcare.

Use Cases of M2M

  1. Smart meters
  2. Asset tracking
  3. Smart factories
  4. ATM 
  5. Telematics 
  6. Vending Machines
  7. HVAC systems 

How does M2M work?

 However, most M2M networks today have a similar setup. As in the example above, you have a device that collects information somehow and relays the information to another device using a network such as WiFi or cellular. At this point, machines, software, or humans may further pass on or interpret the data.

WiFi allows a machine to connect to other machines on the same network or the Internet using a local area network. On the other hand, mobile networks allow machines to be connected over long distances without using a local area network.

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Comparison of IoT and M2M

  • M2M systems use point-to-point communication. On the other hand, IoT systems typically place their devices within a global cloud network and don’t follow point-to-point communication.
  • Scalability is another key difference between M2M and IoT. IoT is designed for high scalability, as devices can often be added to the network and integrated into existing systems with minimal effort, but in M2M, scalability is challenging.
  • Simple device-to-device communication, typically within embedded software at customer sites. Devices communicate using IP networks. Direct communication between machines.
  • In M2M, Communication technology techniques and traditional protocols are used. In IoT, Internet protocols such as HTTP, FTP, and Telnet are used.
  • In M2M, data exchange is only between communicating parties. In IoT, data exchange between other applications improves the end-user experience. 


Fundamentally, M2M is more than just the Internet of Things. M2M includes any wired or wireless machine/device that automatically transmits data. But the intelligent devices that make up the Internet of Things transmit data wirelessly over the Internet. Also, M2M traditionally only referred to peer-to-peer communication between devices. In other words, devices communicate through P2P rather than servers, whereas many IoT devices communicate through a central server.

FAQs - IoT vs M2M

What are the basic definitions of IoT and M2M?

IoT (Internet of Things) refers to a network of interconnected devices that communicate and exchange data through the internet, while M2M (Machine to Machine) involves direct communication between devices, typically for specific tasks, using cellular or wired networks.

How do IoT and M2M differ in terms of connectivity?

IoT devices usually connect using various internet protocols like Wi-Fi, Bluetooth, or 5G, enabling a broader range of connectivity. M2M communication, however, often relies on direct, point-to-point connections using cellular or wired networks.

What is the scope of applications for IoT and M2M?

IoT has a broad scope, encompassing smart homes, healthcare, agriculture, and more. M2M is more focused on specific industrial and business applications like manufacturing and utility management.

Are there differences in data handling between IoT and M2M?

IoT handles large volumes of data and often requires sophisticated data processing, while M2M generally deals with smaller datasets and simpler data transfer and processing.

How does user interaction differ between IoT and M2M systems?

IoT systems often feature user interfaces for interaction and monitoring, accessible via smartphones or computers. In contrast, M2M systems may not prioritize user interfaces, focusing more on machine interaction.

Can both IoT and M2M systems operate autonomously?

IoT devices can often make autonomous decisions based on data analysis. M2M devices usually perform predefined tasks and may require more human intervention for complex decisions.

What is the role of cloud computing in IoT and M2M?

IoT frequently relies on cloud computing for data storage and processing. M2M communication may not always need cloud computing, focusing instead on direct machine interaction.

How do IoT and M2M differ in terms of scalability?

IoT is highly scalable, capable of integrating numerous devices and systems. M2M scalability is more limited, depending on the capacity for direct machine connections.

About the Author
Vikram Singh
Assistant Manager - Content

Vikram has a Postgraduate degree in Applied Mathematics, with a keen interest in Data Science and Machine Learning. He has experience of 2+ years in content creation in Mathematics, Statistics, Data Science, and Mac... Read Full Bio