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

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.

[1]  Kamin Whitehouse,et al.  The hitchhiker's guide to successful residential sensing deployments , 2011, SenSys.

[2]  Adam Dunkels,et al.  Software-based on-line energy estimation for sensor nodes , 2007, EmNets '07.

[3]  Xenofon Fafoutis,et al.  Experiences and Lessons Learned From Making IoT Sensing Platforms for Large-Scale Deployments , 2018, IEEE Access.

[4]  JeongGil Ko,et al.  Wireless Sensor Networks for Healthcare , 2010, Proceedings of the IEEE.

[5]  Patrick Garda,et al.  An Emulation-Based Method for Lifetime Estimation of Wireless Sensor Networks , 2014, 2014 IEEE International Conference on Distributed Computing in Sensor Systems.

[6]  Kyung-Sup Kwak,et al.  The Internet of Things for Health Care: A Comprehensive Survey , 2015, IEEE Access.

[7]  Simon Duquennoy,et al.  TSCH and 6TiSCH for Contiki: Challenges, Design and Evaluation , 2017, 2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS).

[8]  Mani B. Srivastava,et al.  Battery capacity measurement and analysis using lithium coin cell battery , 2001, ISLPED '01.

[9]  Tom Diethe,et al.  Smart-Homes for eHealth: Uncertainty Management and Calibration , 2015, NIPS 2015.

[10]  Robert J. Piechocki,et al.  Internet of Things for smart homes: Lessons learned from the SPHERE case study , 2017, 2017 Global Internet of Things Summit (GIoTS).

[11]  Robert J. Piechocki,et al.  Demo: SPES-2 - A Sensing Platform for Maintenance-Free Residential Monitoring , 2017, EWSN.

[12]  Torsten Braun,et al.  On the Accuracy of Software-Based Energy Estimation Techniques , 2011, EWSN.

[13]  Jan Madsen,et al.  Energy Harvesting - Wireless Sensor Networks for Indoors Applications Using IEEE 802.11 , 2014, ANT/SEIT.

[14]  Laura Marie Feeney,et al.  Towards realistic lifetime estimation in battery-powered IoT devices , 2017, SenSys.

[15]  Lothar Thiele,et al.  Measurement and validation of energy harvesting IoT devices , 2017, Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017.

[16]  Jörg Nolte,et al.  Online Device-Level Energy Accounting for Wireless Sensor Nodes , 2013, EWSN.

[17]  David E. Culler,et al.  Versatile low power media access for wireless sensor networks , 2004, SenSys '04.

[18]  Robert J. Piechocki,et al.  Designing Wearable Sensing Platforms for Healthcare in a Residential Environment , 2017, EAI Endorsed Trans. Pervasive Health Technol..

[19]  Daniele Puccinelli,et al.  Sensor node lifetime: An experimental study , 2011, 2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).

[20]  Anders Lindgren,et al.  How do the dynamics of battery discharge affect sensor lifetime? , 2014, 2014 11th Annual Conference on Wireless On-demand Network Systems and Services (WONS).

[21]  Wendy E. Mackay,et al.  CHI '13 Extended Abstracts on Human Factors in Computing Systems , 2013, CHI 2013.

[22]  Deborah Estrin,et al.  An energy-efficient MAC protocol for wireless sensor networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[23]  Emmanuel Munguia Tapia,et al.  Lessons learned using ubiquitous sensors for data collection in real homes , 2004, CHI EA '04.

[24]  David E. Culler,et al.  Design and implementation of a high-fidelity AC metering network , 2009, 2009 International Conference on Information Processing in Sensor Networks.

[25]  Lars Kai Hansen,et al.  How efficient is estimation with missing data? , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[26]  Amy L. Murphy,et al.  Not all wireless sensor networks are created equal: A comparative study on tunnels , 2010, TOSN.

[27]  Robert J. Piechocki,et al.  Energy-Efficient, Noninvasive Water Flow Sensor , 2018, 2018 IEEE International Conference on Smart Computing (SMARTCOMP).