EpiFi: An In-Home Sensor Network Architecture for Epidemiological Studies

2018_ieee_epifi screenshot

Abstract

We design and build EpiFi, a novel architecture for in-home sensor networks which allows epidemiologists to easily design and deploy exposure sensing systems in homes. We work collaboratively with pediatric asthma researchers to design multiple studies and deploy EpiFi in homes. Here, we report on experiences from two years of deployments in 15 homes, of two different types of studies, including many deployments continuously monitored over the past year. Based on lessons learned from these deployments and researchers, we develop a new mechanism for sensors to bootstrap their connectivity to a subject's home WiFi router and implement data reliability mechanisms to minimize loss in the network through a long-term deplovment

Citation

Philip Lundrigan, Kyeong T. Min, Neal Patwari, Sneha Kasera, Kerry Kelly, Jimmy Moore , Miriah Meyer , Scott C. Collingwood, Flory Nkoy, Bryan Stone, Katherine Sward
EpiFi: An In-Home Sensor Network Architecture for Epidemiological Studies
2018 IEEE 43rd Conference on Local Computer Networks Workshops (LCN Workshops), 2(3): 30-37, doi:10.1109/lcnw.2018.8628482, 2018.

BibTeX

@article{2018_ieee_epifi,
  title = {EpiFi: An In-Home Sensor Network Architecture for Epidemiological Studies},
  author = {Philip Lundrigan and Kyeong T. Min and Neal Patwari and Sneha Kasera and Kerry Kelly and Jimmy Moore and Miriah Meyer and Scott C. Collingwood and Flory Nkoy and Bryan Stone and Katherine Sward},
  journal = {2018 IEEE 43rd Conference on Local Computer Networks Workshops (LCN Workshops)},
  issue_date = {2018},
  numpages = {8},
  publisher = {IEEE},
  doi = {10.1109/lcnw.2018.8628482},
  volume = {2},
  number = {3},
  pages = {30-37},
  month = {Sept},
  year = {2018}
}

Acknowledgements

Research reported in this publication was supported by NIBIB of the US NIH under award number 1U54EB021973-01.