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Batteries and Fuel Cells03:12

Batteries and Fuel Cells

A battery is a galvanic cell that is used as a source of electrical power for specific applications. Modern batteries exist in a multitude of forms to accommodate various applications, from tiny button batteries such as those that power wristwatches to the very large batteries used to supply backup energy to municipal power grids. Some batteries are designed for single-use applications and cannot be recharged (primary cells), while others are based on conveniently reversible cell reactions that...

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An Application for Pairing with Wearable Devices to Monitor Personal Health Status
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Smartphone Sensor Battery Consumption: A Standardized and Reproducible Test Protocol.

Florian Schweizer1,2, Joe Yu2, Elena Mille2

  • 1Institute for Digital Medicine, University Hospital Bonn, University of Bonn, 53127 Bonn, Germany.

Sensors (Basel, Switzerland)
|May 27, 2026
PubMed
Summary
This summary is machine-generated.

We developed a reproducible, low-cost method to test smartphone battery drain from sensors. GPS and camera use significantly impact battery life, with software settings like sampling rate and location accuracy also playing a key role.

Keywords:
iphone hardwarepower consumption in mobile phonessensor power consumptionsmartphone sensors

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Last Updated: May 28, 2026

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Published on: April 30, 2020

Area of Science:

  • Mobile device energy consumption analysis
  • Smartphone hardware and software interaction
  • Reproducible scientific methodology

Background:

  • Accurate measurement of smartphone battery consumption by sensors is crucial for understanding device performance and user experience.
  • Existing methods for battery testing are often costly, lack reproducibility, or do not adequately isolate sensor-specific impacts.
  • Standardized protocols are needed to enable consistent and comparable energy benchmarking across different smartphone models and generations.

Purpose of the Study:

  • To introduce a low-cost, fully reproducible software and hardware protocol for quantifying sensor-specific battery consumption on iPhones.
  • To enable consistent, comparable, and low-cost energy benchmarking across iPhone device generations.
  • To analyze the impact of various sensors (TrueDepth, GPS, accelerometer, pedometer, gyroscope, rear camera) and software parameters (sampling rates, location accuracy) on iPhone battery life.

Main Methods:

  • Development of a standardized protocol including a hardware checklist, light-sealed enclosure, and a dedicated iOS app (BatteryTest) for sensor control and battery state logging.
  • Execution of 30 independent test runs across six iPhone 14 Pro and three iPhone 13 Pro devices.
  • Comparison of battery life outcomes under various sensor conditions, sampling rates, and sensor-specific settings.

Main Results:

  • Baseline battery life was ~10% higher on iPhone 14 Pro compared to iPhone 13 Pro under idle conditions.
  • Sensor activation, particularly GPS and camera usage, substantially reduced battery life.
  • Software parameters significantly influenced battery drain: lower sampling rates decreased battery life, while reduced GPS location accuracy increased it by up to 20 hours on iPhone 13 Pro.
  • Cross-device generation consistency was heterogeneous; iPhone 14 Pro showed longer GPS test battery life but faster camera test drain compared to iPhone 13 Pro.

Conclusions:

  • The presented protocol is the first standardized and fully reproducible method for quantifying sensor-specific battery consumption on iPhones.
  • The findings highlight the significant impact of sensor usage and software configurations on smartphone battery performance.
  • This low-cost approach facilitates consistent and comparable energy benchmarking, aiding in the understanding of battery efficiency across device generations.