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 proceedingConference Contribution (Conference Proceeding)

26 Citations (Scopus)
1248 Downloads (Pure)


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 languageEnglish
Title of host publicationProceedings of the 7th International Workshop on Real-World Embedded Wireless Systems and Networks
PublisherAssociation for Computing Machinery (ACM)
Number of pages6
ISBN (Electronic)978-1-4503-6048-7
Publication statusPublished - 4 Nov 2018

Structured keywords

  • Digital Health


  • Battery-Powered Devices
  • Internet of Things
  • Sensor Deployments


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