Total control: how the IoT surpasses M2M

Even though both machine to machine (M2M) communication and the Internet of Things (IoT) both concern connecting devices to each other, the IoT is built upon fundamentally more interoperable, more scalable, and more modern technologies. Let’s clear up the confusion many people have about each term and explain why they aren’t interchangeable.

From notification to networks

Almost ever since we learned how to tell machines what to do, we’ve wanted to know how they do. Cycle counters, oil gauges, error lights, error messages – all these were designed to either assure us the machine was working well or tell us why it can’t function at all.

Then, we got smarter. We built sensors into the machines and wired them up to a primitive silicon brain, like a programmable logic controller (PLC) or microcontroller. These silicon brains became the central hub of the machine’s nervous system, a simple electronic network which now carried the constant chatter between the sensors and the controller to more general status indicators: LED and LCD alphanumeric displays which reported more specific error and status messages, like “PC LOAD LETTER”, or “no disc”.

Our next step was to make the machines smarter, and so we connected the rudimentary networks inside the machines to larger networks outside the machine. For industrial machines, this led to the wide adoption of wired interfaces like RS-485 and CAN, as well as wireless communication over Zigbee, Xbee, and proprietary cellular networks. While this connectivity became useful for us to remotely access and monitor a device, we quickly discovered the benefits for having large number of machines report their data to another machine, which we would then use to transfer data to and from all the attached devices, as well as to remotely control them. This is the genesis of machine 2 machine (M2M) communication.

And M2M was good. The fact that operations and service personnel could receive real-time operational data from their sensor networks and control systems meant that when a machine failed in the field, they were armed with the data necessary to quickly diagnose the faulty component, replace it, and resume operation.

Breaking out

M2M however, could be better. The device networks are closed to the outside world, and that means those who monitor the machines which in turn monitor a lot more machines have to be physically present in the field or on the premise. Furthermore, these industrial device networks often send and receive messages in their own proprietary format, requiring proprietary software and even equipment to monitor, service, and support the machines on the network.

The Internet of Things (IoT) breaks M2M out of its restrictive niches in two ways. The first is through support of the TCP/IP suite of protocols which allow the machines to send their data not only through the local machine network, but to any other Internet-connected computer on the planet. Secondly, IoT leverages physical interfaces which are based on open standards are agnostic, like Bluetooth, Ethernet, Wi-Fi, 3G, and 4G cellular.

Big data, big capabilities

There’s another way in which IoT devices go far beyond M2M, and that is the integration of advanced analytics: trending, anomaly detection, forecasting, machine learning, and visualization. These are the same tools frequently used for business intelligence (BI), and that’s no mistake, as the cumulative value of all this real-time data from IoT devices is expected to drive increased efficiencies and profits in sectors as diverse as retail, manufacturing, shipping and logistics, and even healthcare.

Just as M2M utilized niche (and often proprietary) protocols, IoT leverages the cloud, where the incoming data meets the scalable processing power, storage, and bandwidth required for performing analytics on the torrent of data in real time. Web interfaces or mobile apps hook onto the cloud, allowing access to all the IoT devices at any time from anywhere via the web.

Connectivity, control, and monitoring are three general areas of overlap between M2M and IoT, but those similarities mask important differences. Where M2M offers networks that are islands and siloed data, IoT delivers integration, comprehensive analytics, and seamless access. While M2M continues to have trouble extending beyond industrial use cases, IoT is already transforming consumer appliances, home security, manufacturing, and logistics. IoT literally brings things onto the Internet, and what in turn do those things bring? The data reveals endless actionable insights and business opportunities.

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