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

X. Fafoutis, A. Elsts, A. Vafeas, G. Oikonomou, R. Piechocki

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.
Reference:
X. Fafoutis, A. Elsts, A. Vafeas, G. Oikonomou, R. Piechocki, "On Predicting the Battery Lifetime of IoT Devices: Experiences from the SPHERE Deployments", in Proc. RealWSN, pp. 7-12, 2018
Bibtex Entry:
@inproceedings{Fafoutis-2018-RealWSN,
  title     = {On Predicting the Battery Lifetime of IoT Devices: Experiences from the SPHERE Deployments},
  author    = {Xenofon Fafoutis and Atis Elsts and Antonis Vafeas and George Oikonomou and Robert Piechocki},
  year      = {2018},
  month     = {11},
  day       = {4},
  doi       = {10.1145/3277883.3277892},
  language  = {English},
  pages     = {7--12},
  booktitle = {Proc. RealWSN},
  publisher = {Association for Computing Machinery (ACM)},
  oa-url = {https://research-information.bristol.ac.uk/en/publications/on-predicting-the-battery-lifetime-of-iot-devices-experiences-from-the-sphere-deployments(05c0efb7-16c9-47fc-b0e1-7fe9dc6f21ec).html},
  gsid = {10336648821840413740},
  doi = {10.1145/3277883.3277892},
  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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