SensingKit: Evaluating the Sensor Power Consumption in iOS devices
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Abstract (arXiv)
Today's smartphones come equipped with a range of advanced sensors capable of sensing motion, orientation, audio as well as environmental data with high accuracy. With the existence of application distribution channels such as the Apple App Store and the Google Play Store, researchers can distribute applications and collect large scale data in ways that previously were not possible. Motivated by the lack of a universal, multi-platform sensing library, in this work we present the design and implementation of SensingKit, an open-source continuous sensing system that supports both iOS and Android mobile devices. One of the unique features of SensingKit is the support of the latest beacon technologies based on Bluetooth Smart (BLE), such as iBeaconand Eddystone. We evaluate and compare the power consumption of each supported sensor individually, using an iPhone 5S device running on iOS 9. We believe that this platform will be beneficial to all researchers and developers who plan to use mobile sensing technology in large-scale experiments.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Jun 2016.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 2.
3 papers.
- 2022Caring Without Sharing: A Federated Learning Crowdsensing Framework for Diversifying Representation of Citiescited by 0
- 2025Cross-platform Prediction of Depression Treatment Outcome Using Location Sensory Data on Smartphonescited by 0
- 2025AnnoSense: A Framework for Physiological Emotion Data Collection in Everyday Settings for AIcited by 0
- 2025AnnoSense: A Framework for Physiological Emotion Data Collection in Everyday Settings for AI17 Jul 2025
- 2025Cross-platform Prediction of Depression Treatment Outcome Using Location Sensory Data on Smartphones10 Mar 2025
- 2022Caring Without Sharing: A Federated Learning Crowdsensing Framework for Diversifying Representation of Cities20 Jan 2022