Researchers explain the energy impact of smartphone system settings

Mon, 04.05.2015

New research results show how to improve your mobile device’s battery lifetime by adjusting system settings.

“Where has my battery life gone?” remains a common source of frustration for many smartphone users. With a high number of adjustable settings on the device, answering this question has become next to impossible, at least until now. The NODES research group from University of Helsinki has studied how the impact of different settings on battery lifetime can be estimated using crowdsourced measurements from a large community of devices. The article “Energy Modeling of System Settings: A Crowdsourced Approach” is published in the 13th IEEE International Conference on Pervasive Computing (PerCom) in St Louis, USA, in March 2015.

Mobile devices have a large number of different adjustable system settings that can be overwhelming for the average user, and even for the expert. Some system settings have a direct and significant correlation with energy consumption, for example screen brightness and network connectivity. The energy impact of other system settings and their combinations can be much more difficult to predict, such as the combination of roaming, high operating temperature, and bad signal strength. The research article demonstrates that the energy impact of these non-trivial system setting combinations can be significant, and presents a new learning based method for assessing this impact.

The published article shows how important it is to model the effects of these different settings as a whole. The research is based on a large dataset that consists of device usage data gathered from over 150,000 smartphones and tablets. The dataset covers real-life daily usage patterns and together with laboratory based specific high precision measurements serves as the empirical basis for the research work.

The proposed energy model for system settings makes it possible to give personalized, practical energy recommendations to the smartphone user. The research findings include the following:

  • Wi-Fi signal strength dropping one bar can cause over 13% battery life loss
  • High temperature can cause even 50% battery life loss, and high temperature is not always related to high CPU load
  • Automatic screen brightness is in most cases better than the manual setting
  • In addition to CPU, battery temperature and distance traveled together offer a good predictor of battery lifetime

The research article “Energy Modeling of System Settings: A Crowdsourced Approach” is available in

More information will be given by professor Sasu Tarkoma, sasu.tarkoma(at) or carat(at)

Contact person: Sasu Tarkoma

Last updated on 28 May 2015 by Maria Lindqvist - Page created on 4 May 2015 by Maria Lindqvist