Battery Health Estimation for IoT Devices using V-Edge Dynamics

Arjun Kumar, Mohammad Ashraful Hoque, Petteri Nurmi, Michael G. Pecht, Sasu Tarkoma, Junehwa Song

Forskningsoutput: Kapitel i bok/rapport/konferenshandlingKonferensbidragVetenskapligPeer review


Deployments of battery-powered IoT devices have become ubiquitous, monitoring everything from environmental conditions in smart cities to wildlife movements in remote areas. How to manage the life-cycle of sensors in such large-scale deployments is currently an open issue. Indeed, most deployments let sensors operate until they fail and fix or replace the sensors post-hoc. In this paper, we contribute by developing a new approach for facilitating the life-cycle management of large-scale sensor deployments through online estimation of battery health. Our approach relies on so-called V-edge dynamics which capture and characterize instantaneous voltage drops. Experiments carried out on a dataset of battery discharge measurements demonstrate that our approach is capable of estimating battery health with up to 80% accuracy, depending on the characteristics of the devices and the processing load they undergo. Our method is particularly well-suited for the sensor devices, operating dedicated tasks, that have constant discharge during their operation.

Titel på gästpublikationProceedings of the 21st International Workshop on Mobile Computing Systems and Applications : HotMobile'2020
Antal sidor6
UtgivningsortNew York
Utgivningsdatum4 mar 2020
ISBN (elektroniskt)978-1-4503-7116-2
StatusPublicerad - 4 mar 2020
MoE-publikationstypA4 Artikel i en konferenspublikation
EvenemangHotMobile '20: The 21st International Workshop on Mobile Computing Systems and Applications - Austin, Förenta Staterna (USA)
Varaktighet: 3 mar 20204 mar 2020
Konferensnummer: 21


  • 113 Data- och informationsvetenskap
  • 213 El-, automations- och telekommunikationsteknik, elektronik

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