The Difference Between M2M and IoT

Tim Taberner, Global Product Manager, Advanced IoT GatewaysRecently, while visiting another company that works in the IoT space, I got into a discussion with one of their technical leads. We were talking about the difference between M2M and IoT, and his view was that they were essentially the same thing. As far as he was concerned, IoT merely adds new sensors to collect data at lower price points, and more powerful computation capabilities at the enterprise to enable massive data mining and analytics. He summed it up by saying something along the lines of, “We measure the data with new sensors, we transmit it to the enterprise, and then some clever people do clever things to transform the data into actionable information”.

He was completely missing some of the fundamental differences between the “old” M2M and the “new” IoT architectures. In particular, he seemed to be overlooking the ways in which IoT pre-processes data at the network edge before sending it on for consumption; and in the things IoT does as it transmits the data to the enterprise’.

Traditional M2M systems have typically been applied to the monitoring, control or optimization of a single process. They have been specified, designed and implemented to address a point-in-time problem with a point-in-time solution. Using the old M2M architecture, for example, a building might have separate systems for HVAC control, security and fire detection. Quite often, these discrete systems will take the same measurements at the same places via separate sensors. The sensors are wired back to separate instrumentation cabinets, and then to separate operator screens. Each system will communicate internally using its own (often proprietary) protocols and standards.  Sharing data between systems is difficult, often impossible.

On the positive side, it has been relatively easy to specify M2M systems. When we’re dealing with a point-in-time problem we can scope out the measurements that we need to make, and the way we want this information summarized. The boundaries of what we want to achieve can be defined, and an ROI case is relatively simple to justify (or reject).
M2M System DiagramA traditional M2M system can be thought of as a manager sitting in an office, constantly contacting his team of remote workers in a never ending cycle.  The manager asks if everything is ok, and deals with any events that crop up.  To do this, the manager must know how to contact and exchange information with each of his workers. And because of the repetitive nature of the inquiries, and the limited topic of the discussion, they all use a ‘shorthand’ language that they mutually understand.  This allows them to communicate quite efficiently between themselves.  But their language is not easily understood in the wider world, and it cannot easily adapt to new situations and use cases.

IoT on the other hand, is about systems of systems. It’s about producers of data publishing information without needing to know what applications or users will be consuming that data. It’s about making data available to multiple systems in a way that can be expanded and revised as new requirements emerge. It’s about being able to investigate dependencies and causality between seemingly unrelated data feeds. It’s about optimizing not just a single process, but optimizing an entire ecosystem, and having the ability to adapt and evolve as new requirements and use cases emerge.  It’s about repurposing data, and combining it freely without having to define everything that we want to do on the first day of the project. The initial use case may justify the ROI for the system, but we don’t necessarily have to know how we want to expand the system in the future. IoT architectures need to provide this flexibility, which has never been a major consideration in traditional M2M.

IoT System DiagramThink of it as being “Twitter for machines”. If I am a device, all I have to do is subscribe to a topic of interest.  I don’t need to know who is tweeting, or how they are connected to the network.  I simply receive the relevant information, and I can then determine what to ignore and what to act upon. Other devices that are interested in the same topic, for reasons of their own, can also choose to follow it. Like me, they will receive the information without having to make any changes to the producers of the information.  And they can do it without affecting me and what I am doing.  New devices can subscribe to the data at any time, and existing devices can unsubscribe at any time. None of these devices interfere with one another. Similarly, additional producers of information can come online at any time and begin contributing their information to the knowledge pool.

Many kinds of data are mission critical, of course. And in the IoT world, information is being transferred without human intervention. Our security and recovery procedures need to be very robust. We also need topic definitions that have finer granularity than a simple hashtag.

Let’s come back to the engineer who inspired this blog, and his comment that “we transmit it to the enterprise”.

His comment ignored the critical contribution made to IoT architecture by the edge device located at each remote asset. Unlike traditional M2M equipment like RTUs, PLCs or simple routers, IoT edge devices provide data processing functions before passing the data along.  The IoT edge device not only provides the physical network interface for lower order devices and sensors, it provides the necessary translation as well as the decoupling between the data recovered from these systems and the information sent to the enterprise.

  • It filters out data with little or no value. (Example: “The temperature in the room I’m in is the same as it was 10 seconds ago – do I really want to pass this information on to this enterprise system?”)
  • It aggregates this into summary data. (Example: Min, mean and max temperature values in the room each hour.)
  • It provides event detection. (Example: The temperature goes beyond a threshold, or has an unexpectedly rapid rate of change. Significant data like this can be prioritized and sent immediately.)
  • It provides data enrichment, contextualizing information into something which is self defining and semantically searchable. (Rather than sending “PLC31 register 40072 has a value of 2078” it would send something like “B+B Galway / Tims office {date: 1 Dec 2015, time: 10:40, temperature: 20oC.)
  • It provides communications management and security around the data transactions.
  • It allows user business logic to be embedded in the edge device to provide highly responsive local intelligence.

It’s very easy to talk about IoT while missing the devil in the detail. “We send the data to the enterprise” is a very obvious example of this. If you really want to know the difference between M2M and IoT, consider the phrase, “I don’t know what I don’t know”.  M2M systems have historically ignored the unknown, whereas IoT architectures embrace it.

Tim Taberner
Global Product Manager, Advanced IoT Cellular Gateways

 

8 thoughts on “The Difference Between M2M and IoT

  1. brian M

    Think the person you were talking had a fair handle on IoT ! Its just a bigger version of M2M or P2P (take that as the web)

    First there is no real standard for IoT its a marketing/journalist persons concoction , maybe some standards might appear, but there will be no universal language for everything – and probably better If there wasn’t anyway for security!

    Perhaps sub-sectors of industry/users might have a standard which they all understand (think CAM bus or NMEA 0183) often it will be kept proprietary such as NMEA 2000 and only revealed to those that can afford to join the club.

    Perhaps the best analogy would be XML, anyone can read the data – but then you have to know its meaning and context or TV remotes (nightmare!).

    Maybe the only commonality will be the transfers layers, protocols etc. such as IP/TCP or IP/UDP (two differences all ready) but the physical layers will need to be different depending on use low power/ultra low power or a lot of power for pre-processing.

    Best thing is not to give it a name its just a networked device (full of potential security threats!).
    Or perhaps as one joker said IoT – the Internet of trouble!

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  2. Chris Dobson

    The explanation of IoT sounds a lot like OPC. I have worked on systems (15 – 20 years ago) that did precisely what you are describing as IoT, without OPC. I am still confused. To me, it sounds like IoT is just a new name for an older concept…….. The only difference that I see is that instead of sensors being read by a PLC which then passes on the data, the sensors would pass on the data themselves.??

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  3. Milena Gherardi

    I find it very interesting. I am not a technical people so I never went too deep into M2M, OPC or any other technical concept but I think I really got the explanation !! He is not saying that M2M and IoT have nothing to do with each other but that IoT in a real evolution bith in technology and in the scope itself!

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  4. Chukwuma Igbogbahaka

    Great article. It would have helped to define M2M and IoT at least once at the beginning possibly. Job well done nonetheless.

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  5. Bill Ingle

    Good article but the distinction between M2M and IoT is somewhat artificial — M2M grew up simultaneously in many vertical industries with many vertical-unique acronyms and technologies; the term itself was somewhat artificial when it was used as the label for an industry (artificial but handy — shorter than “smart” this or that, or the “intelligent networked devices” phrase used in the late 90s and early 2000s here and there). These technologies never stopped changing, as the miniaturization of electronics continued and continues, a process that began long before either acronym was invented.

    “Traditional M2M” thus refers to limited moments in different verticals even while offerings here and there were already stretching outside those moments and deploying new types of solutions. Early examples of edge processing can be found in some of the verticals dating to those days before “IoT” became as commonly used as it is today (look at certain M2M cellular and satellite terminals incorporated into modules with processors, various “M2M gateways” or even some of IBM’s early “smart planet” solutions). Someone else might just as well describe IoT as “evolved M2M.”

    Meanwhile, any number of former M2M service and solution providers have simply changed “M2M” to “IoT” in their product and marketing literature even as the technologies and solutions they deploy continue to evolve.

    It’s probably just a matter of time before we start seeing “traditional IoT” or someone, describing their company’s latest offering at an industry conference, claims it’s “not your grandfather’s IoT.”

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  6. Manjunath Mahashetti

    Hi,

    i would like to Charactreise M2M as more of internal Information management and process control of an Enterprise and related Industries. Say, a manufacturing industry with Supply chain handling backward and Forward integration. but IOT is a bigger system in Scope of operations . One example, which is my favourite, is the Energy metering and Management. Let us suppose all domestic houses have Smart Meter. this Smart Meter has feature where it can recieve messages from Electrical Supply Company. This utility company publishes the price of Electrical Energy unit price at different times in a day. Obviously Peak charges at Morning (When people go to offices, Children go to school) etc will be very high. The Electricity Tarrif will be lower at 3:00 or 4:00 AM, 11:00 AM-3:00 PM etc. So The System will tell the Water Heater to switch on at 3:00 AM and Keep hot water Ready, Switch on the Washing Machine at 11:00 am etc when Tarrifs are low. Also the Hiuse System reads the Weather Report and take decisions on How to manage the AC.
    So in essence it is the Interplay of many system, that are Logically seperate and Can Exist without each other, but can join together to make decisions, which helps in increase optimal use. The Systems will also have flexiblities to add any new feature relating to product and services. The System also may use the advanced analytical or Machine Learning to have the optimazation.

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