Predictive data, the real workhorse behind the Internet of Things

It's not just about collecting mounds of data anymore, but analyzing it to make smart decisions.

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Daikin also uses a power meter that monitors the supply coming into the unit. Via the gateway, it sends data about the power signal to an Intel cloud, where it's analyzed to determine the power usage of each component inside the HVAC system, like fans and refrigerant compressors.

Without the back-end analytics, Daikin would have to install meters on each component, an implementation that would be prohibitively expensive, Facinelli says.

   Daiken rooftop unit
Daikin's commercial Rebel cooling or heat pumps allow property owners to track energy consumption . . .

Once the component energy use data is available, it's sent to Daikin's cloud, running on Microsoft Azure, where Daikin uses it for fault detection and diagnoses and to predict if the equipment needs maintenance.

Many businesses have been collecting data about equipment in the field for years. But what's new now is that they can collect enough data, and the right kind of data, to do predictive analytics.

Daikin's energy app
. . . by means of an app like this one.

At Daikin, the data about individual component use of energy is very valuable.

"Over time if you see energy increasing for a motor, it can be a good indication that the motor is starting to fail," Facinelli says. Technicians have enough advance warning, probably a month, before the failure happens so they can service the unit before problems start.

The energy use data also means Daikin can change filters only when needed, rather than on a regular schedule. That's because components like the fan have to work harder, pulling more energy, when pollen and other material clog the filter. "Instead of changing the filter every week or every month, we do it when it needs it, based on performance," he says.

Daikin and its partners have been working on its system, including the gateway and the power meter, for about a year and have six installed systems as a field trial. The technology will be built into all units going forward and can be retrofitted into units built since 2008.

A number of technologies had to be available for the companies to build this system. Mobile, cloud, analytics and a good user experience were all necessary, Facinelli says. "It isn't about a lot of data but about contextualizing it for the user," he says.

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