Evidence map›Paper›PMID 42197733›Full record

ArticleSensors (Basel, Switzerland)2026

Smartphone Sensor Battery Consumption: A Standardized and Reproducible Test Protocol.

Florian Schweizer, Joe Yu, Elena Mille, Lara Marie Reimer, Maximilian Kapsecker, Jens Klinker, Stephan Jonas

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Florian SchweizerInstitute for Digital Medicine, University Hospital Bonn, University of Bonn, 53127 Bonn, Germany.ORCID 0009-0001-2902-5178
Joe YuTUM School of Computation, Information, and Technology, Technical University Munich, 85748 Garching near Munich, Germany.ORCID 0009-0003-8647-8848
Elena MilleTUM School of Computation, Information, and Technology, Technical University Munich, 85748 Garching near Munich, Germany.ORCID 0009-0005-3072-5760
Lara Marie ReimerInstitute for Digital Medicine, University Hospital Bonn, University of Bonn, 53127 Bonn, Germany.ORCID 0000-0002-6546-8531
Maximilian KapseckerTUM School of Computation, Information, and Technology, Technical University Munich, 85748 Garching near Munich, Germany.ORCID 0000-0002-3907-0749
Jens KlinkerTUM School of Computation, Information, and Technology, Technical University Munich, 85748 Garching near Munich, Germany.ORCID 0009-0003-1054-8117
Stephan JonasInstitute for Digital Medicine, University Hospital Bonn, University of Bonn, 53127 Bonn, Germany.ORCID 0000-0002-3687-6165

Funding

Bundesministerium für Forschung, Technologie und Raumfahrt 01IS17049
6 · The paper itself

Abstract

We present a low-cost, fully reproducible software and hardware protocol for smartphone sensor battery cost tests. Our pipeline combines a rigorous hardware checklist and light-sealed enclosure, a software checklist for iOS devices, and a BatteryTest app to control sensor configurations and log battery state during tests. Methodologically, we applied this standardized protocol in 30 independent analyzed test runs using six iPhone 14 Pro and three iPhone 13 Pro devices, and compared battery-life outcomes across predefined sensor conditions (idle, TrueDepth, GPS, accelerometer, pedometer, gyroscope, and rear camera), sampling rates, and sensor-specific settings. Key findings include: (i) Baseline battery life was approximately 10% higher on the 14 Pro versus the 13 Pro models under idle conditions. Sensor activation substantially reduced battery life, with GPS and camera usage exhibiting the strongest impact. (ii) Software parameters matter: the sampling rate change from 27 s to 3 s led to significantly decreased battery life in several scenarios, while reducing the location accuracy in GPS tests increased battery life by up to 20 h on the 13 Pro devices. (iii) Cross-device-generation consistency is heterogeneous. The iPhone 14 Pro lasts up to 50% longer on GPS tests, yet drains about an hour faster than the 13 Pro in camera tests. This work introduces the first standardized, and fully reproducible protocol for quantifying sensor-specific battery consumption on iPhones, enabling consistent, comparable, and low-cost energy benchmarking across device generations.

Indexed as

iphone hardwarepower consumption in mobile phonessensor power consumptionsmartphone sensors

Identifiers

PMID42197733
PMCPMC13211051

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.