EpiFi: An In-Home Sensor Network Architecture for Epidemiological Studies
Philip Lundrigan, Kyeong Min, Neal Patwari, Sneha Kasera, Kerry Kelly,, Jimmy Moore, Miriah Meyer, Scott C. Collingwood, Flory Nkoy, Bryan Stone, and, Katherine Sward

TL;DR
EpiFi is a novel in-home sensor network system designed to simplify deployment for epidemiological research, featuring easy configuration, reliable device discovery, secure sensor authentication, and data integrity for long-term studies.
Contribution
It introduces a new architecture with simplified setup, secure sensor authentication, and data reliability mechanisms tailored for epidemiological in-home studies.
Findings
Successfully deployed in homes for pediatric asthma research
Enhanced device discovery and authentication methods
Achieved reliable long-term data collection
Abstract
We design and build a system called EpiFi, which allows epidemiologists to easily design and deploy experiments in homes. The focus of EpiFi is reducing the barrier to entry for deploying and using an in-home sensor network. We present a novel architecture for in-home sensor networks configured using a single configuration file and provide: a fast and reliable method for device discovery when installed in the home, a new mechanism for sensors to authenticate over the air using a subject's home WiFi router, and data reliability mechanisms to minimize loss in the network through a long-term deployment. We work collaboratively with pediatric asthma researchers to design three studies and deploy EpiFi in homes.
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Taxonomy
TopicsHealth, Environment, Cognitive Aging · Context-Aware Activity Recognition Systems · Mobile Health and mHealth Applications
