Abstract
A data collection infrastructure is vital for generating sufficient amounts and diversity of data necessary for developing algorithms in home-based health monitoring. However, the manageability - deployment and operation efforts - of such an infrastructure has long been overlooked. Even a small size of a dozen homes may incur enormous manual efforts on the research team. In this article, we present Proteus, an easily managed infrastructure designed to automate much of the work in deploying and operating such systems. We develop new components and combine with mature technologies to minimize the human efforts required. Proteus includes: 1) scalable, continuous deployment, operation, and update of devices with automatic bootstrapping; 2) automatic fault and error monitoring and recovery with watchdogs and LED feedback, and complementary edge and cloud storage backups; and 3) an easy-to-use data-agnostic pipeline for integrating new modalities. We demonstrate our system's robustness through different sets of experiments: three sensor nodes (SNs) running for 24 days sending data (17.4 Mb/s aggregate rate), 10 SNs for 14 days (58 Mb/s aggregate rate), and 32 emulated sensors (419.2 Mb/s aggregate rate). All such experiments have data loss rates less than 1%. Further we reduce human efforts by 25-fold and code required for adding new data modality by 25-fold. We also share our experience and lessons learned during the design, development, and pilot deployment of Proteus. Our results show that Proteus is a promising solution for enabling research teams to effectively manage home-based health monitoring at small to medium sizes.
| Original language | English |
|---|---|
| Pages (from-to) | 1125-1136 |
| Number of pages | 12 |
| Journal | IEEE Internet of Things Journal |
| Volume | 12 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2025 |
Keywords
- Application platform
- connected health
- data collection infrastructure
- device management
- home-based health monitoring
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