Do IoT Applications Need Intelligent Sensors?

Internet of Things applications can be complex, and many engineers are now searching for better ways to deal with the massive amounts of data coming from IoT sensors.

Internet of Things (IoT) applications can be complex, and many engineers are now searching for better ways to deal with the massive amounts of data coming from IoT sensors.

For many, the choice of a computing architecture is critical. They can employ a centralized model, where they send mountains of raw data to the cloud, or can they use an edge-based model, where they place electronic intelligence at the sensor.

To learn more about the choices, Design News spoke with Analog Devices, Inc. engineers, Grainne Murphy and Ian Beavers. Murphy, an IoT marketing manager for ADI, is an engineering graduate of the University of Limerick and holds an MBA from Oxford Brookes University. Beavers, an applications engineer for the high-speed converter team at ADI, holds a BS in electrical engineering from North Carolina State University and an MBA from the University of North Carolina at Greensboro.

DN: Why is it important to be talking about IoT computing architectures right now?

Murphy: My personal opinion is that the IoT has been dominated by a discussion of the cloud – it’s been all about analytics and software companies. And so we see a lot of people doing proof of concept, and they have great ideas, but they don’t really know what to do with them. And maybe the data isn’t good enough to provide value to the end customer.

So right now, you’ve got to determine what you want to achieve with an IoT system, and then work backward to determine what kind of system you really want.

ADI Marketing Manager Grainne Murphy: “We’ve been talking about (the edge-based model) with people for the past year, and we’re hearing it more and more.” (Source: ADI)

DN: Do today’s industrial IoT applications typically use a centralized architecture or an edge-based computing model?

Beavers: It depends on whether it’s a “green field” or “brown field” network.

In a green field, you can bring in new [technology] and not be beholden to an incumbent network. You can develop something from scratch that fits the application. Some of the new IoT systems that we are bringing to market are edge-based. They can allow decisions and outcomes to happen that weren’t possible before.

Whereas, with a brown field network, you may have to work with the existing infrastructure. So you may have a centralized network there.

DN: What does the edge-based model look like in terms of hardware?

Beavers: Let’s take a machine condition-monitoring example, where you’re monitoring a large piece of equipment in a factory. There, you could have three-axis accelerometers doing the sensing. The measurement would be done by some kind of FFT (fast Fourier transform). And you could interpret the data to determine if you crossed some kind of threshold, and decide if it needs to be addressed.

In that application, you could have real-time decisions done right there at the edge. So you don’t need to send all the data downstream. It’s less than 1% in some cases. If we sent all the data downstream, the bandwidth needs would be extremely large, especially if you

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