Differences between M2M and the IoT

The Internet of Things (IoT) is increasingly taking over from Machine-to-Machine communications (M2M) as the trendy new buzzword. However, these terms are often used interchangeably, and neither of these two popular terms is well defined or standardised, with many organisations and companies operating with their own internal definitions. So, what’s the difference between IoT and M2M?

In a basic sense, the definition of Machine-to-Machine communications (M2M) is that it’s communication between one remote machine and another. M2M is basically about communicating with a remote machine in the field in order to manage that machine or collect machine and sensor data.

M2M connectivity has been used in industry in one form or another long before the Internet in its modern form has been around, usually through the use of embedded modems and the wired or cellular telephone networks.

As an example of a familiar embedded M2M system, which has been in use for a long time, consider the point-of-sale EFTPOS terminal in a shop, which communicates with the bank, commonly over the telephone network. This system is networked from point A to point B, with a specific job to do.

When it comes to the maintenance of vending machines or industrial machines, M2M capabilities allow the vendors of machines or assets to reduce service and management costs through remote diagnostics, troubleshooting, updates and similar remote maintenance which optimises the deployment of service personnel in the field, deploying personnel only when they’re needed.

The scope of industrial M2M also includes industrial telemetry and remote surveillance of systems such as SCADA equipment.

M2M can be understood from a more vertical perspective, usually built around proprietary, closed systems, whilst the IoT encompasses a more horizontal and interoperable approach where vertical applications are pulled together in order to provide value for both business and end users.

While M2M solutions offer remote communications with machines, this data is traditionally targeted at specific, closed solutions that perform specific applications. Rarely, if ever, is the data integrated with enterprise applications to help improve overall business performance, and this is where more complicated IoT applications can realise gains both in terms of user and business value.

If you can recognise whether you seek a point solution for simple remote machine access, such as a service-management application, or you seek to drive incremental business benefits across the enterprise through the use of analytics, Big Data and other software-oriented tools for the improvement of business performance, both from the business perspective and customer perspective, then you can recognise whether a machine-to-machine application or an Internet-of-Things application is what you’re looking for to best suit your needs.

The IoT represents things connecting with systems, people and other things, moving beyond connectivity from one machine to another. “Things” in the IoT can include machines, sensors, consumer products, appliances, vehicles and systems that control other physical devices, but they can also include CRM systems and analytics applications, data warehouses or other business intelligence systems.

Internet-of-Things applications and platforms can interconnect data between things, systems and people, connecting things to other things as well as cloud computing infrastructure, people, and business systems.

But there is some overlap between modern IoT systems and M2M systems, since every modern IoT system must have some kind of machine-to-machine communications links somewhere. You might say that today M2M systems are a subset of the Internet of Things, but the IoT has a much broader scope than traditional M2M connectivity.

Things and systems in the Internet of Things are also interconnected into people – consumers and end users as well as business decision makers.

Integration of device and sensor data with big data, analytics and other enterprise applications is a core concept behind the Internet of Things and this integration is key to achieving many potential new IoT benefits throughout industry. IoT devices communicate using open standards, in many cases, and this use of open standards is a key driver behind the success of the Internet of Things, just like the Internet has been built around open standards with great success.

This use of open standards, and room for interoperability, is a key factor that differentiates the IoT from the older domain of industrial M2M telemetry, which is often proprietary and vendor-specific, with the communication from a remote machine being tied back to one fixed place for one fixed application at one specific operator or site.

The data collected by Internet-of-Things services and devices can be incorporated into enterprise applications to enable improved service but also improved business intelligence, operational improvement and indeed the generation of whole new business models.

The ability for applications throughout the enterprise to access device data to enable performance improvements and business innovation clearly distinguishes the potential of IoT technologies from traditional point-to-point M2M communications.

IoT applications typically rely on IP-based networks to interface device data to a cloud or middleware platform accessible from the Internet, enabling access to this data by any enterprise application, anywhere, that is authorised to do so.