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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
Summary
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.
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.
