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​Google: Here’s how we predict battery life based on your usage patterns

Video: Pixel 2 and Pixel 2 XL review

Google is using machine learning to improve the accuracy and credibility of its battery-life predictions on the Pixel.

If you felt your Pixel’s battery life forecasts were previously inaccurate, you can blame the assumptions Google used to make about usage.

A Google product manager has now explained on the Pixel forum that the company used to assume that if you had used up 10 percent over the past few hours, it estimated that level of per-hour usage would remain consistent.

“As you might expect, this wasn’t always very accurate,” wrote a product manager called Michelle from Google’s NYC office.

To improve accuracy, Google has created an ‘on-device model’ that analyzes each device’s battery usage over time to build an understanding of patterns of usage on similar days and times.

That way it can personalize predictions based on how an individual uses the phone, factoring frequent and predictable usage spikes such as might be observable if that person likes watching Netflix or YouTube during the daily commute home.

The Battery section in Settings displays both the percentage of battery life remaining and an estimate of how many hours and minutes this translates to, based on the model’s analysis of usage patterns.

Long-pressing the Battery icon displays ‘Advanced battery usage’, which shows a graph of estimated battery life, including the number of hours since it was fully charged and hours before the battery will be fully depleted.

The graph will also reflect how Google’s model predicts high and low usage as seen in steeper and flatter portions of the graph.

As Android Authority notes, the now built-in feature looks related to a distinct app that Google was working on in October called Device Health Services, which calculated remaining battery life based on usage. It was on the Google Play Store but is not currently available.

Pixel users are getting more accurate battery-life predictions, based on usage patterns.


Image: Google

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