On Predicting the Battery Lifetime of IoT Devices: Experiences from the SPHERE Deployments

Xenofon Fafoutis; Atis Elsts; Antonis Vafeas; George Oikonomou; Robert Piechocki

doi:10.1145/3277883.3277892

On Predicting the Battery Lifetime of IoT Devices: Experiences from the SPHERE Deployments

Xenofon Fafoutis, Atis Elsts, Antonis Vafeas, George Oikonomou, Robert Piechocki

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

28 Citations (Scopus)

1376 Downloads (Pure)

Abstract

One of the challenges of deploying IoT battery-powered sensing systems is managing the maintenance of batteries. To that end, practitioners often employ prediction techniques to approximate the battery lifetime of the deployed devices. Following a series of longterm residential deployments in the wild, this paper contrasts real-world battery lifetimes and discharge patterns against battery lifetime predictions that were conducted during the development of the deployed system. The comparison highlights the challenges of making battery lifetime predictions, in an attempt to motivate further research on the matter. Moreover, this paper summarises key lessons learned that could potentially accelerate future IoT deployments of similar scale and nature.

Original language	English
Title of host publication	Proceedings of the 7th International Workshop on Real-World Embedded Wireless Systems and Networks
Publisher	Association for Computing Machinery (ACM)
Pages	7-12
Number of pages	6
ISBN (Electronic)	978-1-4503-6048-7
DOIs	https://doi.org/10.1145/3277883.3277892
Publication status	Published - 4 Nov 2018

Research Groups and Themes

Digital Health
SPHERE

Keywords

Battery-Powered Devices
Internet of Things
Sensor Deployments

Access to Document

10.1145/3277883.3277892

Full-text PDF (accepted author manuscript)
This is the author accepted manuscript (AAM). The final published version (version of record) is available online via ACM at https://dl.acm.org/citation.cfm?id=3277892 . Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 4.1 MB

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SPHERE (EPSRC IRC)
Craddock, I. J. (Principal Investigator), Coyle, D. T. (Principal Investigator), Flach, P. A. (Principal Investigator), Kaleshi, D. (Principal Investigator), Mirmehdi, M. (Principal Investigator), Piechocki, R. J. (Principal Investigator), Stark, B. H. (Principal Investigator), Ascione, R. (Co-Principal Investigator), Ashburn, A. M. (Collaborator), Burnett, M. E. (Collaborator), Damen, D. (Co-Principal Investigator), Gooberman-Hill, R. (Principal Investigator), Harwin, W. S. (Collaborator), Hilton, G. (Co-Principal Investigator), Holderbaum, W. (Collaborator), Holley, A. P. (Manager), Manchester, V. A. (Administrator), Meller, B. J. (Other ), Stack, E. (Collaborator) & Gilchrist, I. D. (Principal Investigator)
1/10/13 → 30/09/18
Project: Research, Parent

End to End System Optimisation of Wireless Interconnected Sensors for Healthcare Monitoring at Homes: Advancements in multimodal sensing technology for healthcare in residential environments
Vafeas, A. T. (Author), Oikonomou, G. (Supervisor), Piechocki, R. J. (Supervisor) & Craddock, I. J. (Supervisor), 21 Jan 2021
Student thesis: Doctoral Thesis › Doctor of Philosophy (PhD)

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Cite this

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abstract = "One of the challenges of deploying IoT battery-powered sensing systems is managing the maintenance of batteries. To that end, practitioners often employ prediction techniques to approximate the battery lifetime of the deployed devices. Following a series of longterm residential deployments in the wild, this paper contrasts real-world battery lifetimes and discharge patterns against battery lifetime predictions that were conducted during the development of the deployed system. The comparison highlights the challenges of making battery lifetime predictions, in an attempt to motivate further research on the matter. Moreover, this paper summarises key lessons learned that could potentially accelerate future IoT deployments of similar scale and nature.",

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On Predicting the Battery Lifetime of IoT Devices: Experiences from the SPHERE Deployments. / Fafoutis, Xenofon; Elsts, Atis; Vafeas, Antonis et al.
Proceedings of the 7th International Workshop on Real-World Embedded Wireless Systems and Networks . Association for Computing Machinery (ACM), 2018. p. 7-12 .

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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AU - Piechocki, Robert

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KW - Sensor Deployments

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M3 - Conference Contribution (Conference Proceeding)

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PB - Association for Computing Machinery (ACM)

ER -

On Predicting the Battery Lifetime of IoT Devices: Experiences from the SPHERE Deployments

Abstract

Research Groups and Themes

Keywords

Access to Document

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Projects

SPHERE (EPSRC IRC)

Student theses

End to End System Optimisation of Wireless Interconnected Sensors for Healthcare Monitoring at Homes: Advancements in multimodal sensing technology for healthcare in residential environments

Cite this