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Exploring the Difference Between M2M and IoT

Posted by Gordon Van Huizen on Jul 22, 2015 12:00:00 AM

Amid all the buzz around the Internet of Things (IoT), there can be a lot of confusion about how the vision of IoT relates to the more established and proven concept of machine-to-machine (M2M) communication. Given that M2M is all about connecting devices, it’s easy to think the distinction is all hype—or, conversely, that the grand vision for IoT is simply too “blue sky.” Either way, those steeped in M2M implementation may conclude that IoT is the latest “emperor’s new clothes” of the technology world. The reality is that while the aspirations for IoT are indeed sweeping, there are identifiable advancements inherent in IoT that already provide tangible value. And, fortunately, businesses already leveraging M2M are well positioned to benefit from IoT’s additional capabilities.

In an earlier DSI Labs post, we quoted Jacob Morgan writing for Forbes with the definition of IoT simply as “…the concept of connecting any device with an on and off switch to the Internet (and/or to each other).” A grand vision indeed. M2M, on the surface, would appear to be a fundamentally required capability—and it is. But a world of connected sensors and smart machines requires a lot more. Most M2M deployments involve either a small, fixed number of devices or a small number of device types. Device communication is often performed over proprietary hardware and software through custom integration efforts. And M2M applications are often purpose-built, with a great deal of awareness of the devices they leverage baked into the application code itself. The vision for IoT is much broader and interconnected, striving toward a future where large numbers of heterogeneous devices communicate in a much more dynamic—and potentially intelligent—way. Making this vision a reality requires a different way of thinking about the problem and a different architecture to support it.

M2M Integration: Purpose-Built for Success

For decades, though, M2M integrations have automated processes in many industries. Perhaps more than those in any other segment, manufacturing and distribution companies have long used M2M to automate and optimize processes—connecting machines to streamline production on the shop floor, to monitor and control warehouse operations and to automatically sense when fuel must be replenished, among other uses. In these scenarios, M2M connections facilitate communication between a small number of devices (e.g., weight scales or conveyor systems) and are purpose-built to automate specific tasks or processes.

DSI’s extensive background in M2M implementation includes a vast array of integrations to optimize business processes on the shop floor, in the warehouse and in the field. Our latest M2M case study provides a manufacturing and distribution example in which a major food manufacturer deployed DSI’s platform to integrate multiple enterprise software systems. Using DSI’s M2M communication to connect their automated material handling system, unitizers, automated guided vehicles and a seven-level, high-density racking system, the company eliminated user intervention for a truly automated process and uninterrupted flow of materials. These M2M connections are secure and reliable, with lasting benefits, though the tasks performed are fixed in their relationship to work processes and the people using them.

The Best of Both Worlds: IoT and M2M

Industrial IoT builds upon this foundation. Supporting a large, potentially dynamic number of individual devices—thermal sensors and GPS devices mounted on truck fleets, for example—requires device management: the ability to add and remove devices in the field and associate them with supply chain data. Connectivity across an increasing array of device types requires standards-based protocols. And developing software solutions that can be leveraged across multiple IoT implementations requires a more horizontal, generalized software stack, one that implements the core requirements and design patterns of Industrial IoT, while supporting new types of devices and new use cases.

These additional IoT capabilities provide significant, tangible value within the supply chain. For a large brand like the one mentioned in our earlier example, IoT might connect not only the machines and software in the warehouse, but also other sensors and devices upstream and downstream in the supply chain. In an IoT-enabled supply chain, users would have a 360-degree view of the value network, with data collected from a broad network of connected sensors and machines presented as actionable information in real time. For instance, in the manufacturing plant or in the field, connected machines can relay information to enable predictive maintenance—thereby optimizing asset management and service delivery. Downstream in the supply chain, advancements in IoT could provide in-transit visibility into the precise location of deliveries as well as monitor and ensure their temperature stability.

While M2M integrations demonstrate proven benefits, the broader functionality of IoT promises greater flexibility and capability in an increasingly competitive market. Continue exploring DSI Labs to see other DSI M2M implementations in action, and for more updates on IoT.

Topics: m2m

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