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Home-based health monitoring systems are important to many conditions (e.g., aging, chronic diseases). The absence of suitable data collection infrastructure is a fundamental barrier to the development of related algorithms and systems. In this poster, we present Proteus, a robust, extensible and scalable data collection infrastructure, to enable small research teams to manage large deployments. We identify the desired features and achieve them by combining mature technologies and new components: i) extensibility with new, diverse sensor types and data formats with a few lines of coding (LOC) efforts; ii) scalability in managing sensor/edge devices to automate many deployment, management tasks; iii) resilience to system failures and network outage. Experiments on a prototype show zero data loss or system error for one sensor node running 10 days, and 99.95% of data received for 32 emulated sensors sending data at 200 Mbps, 20 and 100 fold reductions in node setup efforts and LOC for new sensor types. The preliminary results show Proteus is promising for large-scale longitudinal deployment of home-based health monitoring.
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Proteus: Towards a Manageability-focused Home-based Health Monitoring Infrastructure
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, including installing, configuring and updating of sensor, edge devices; continuous monitoring for faults and errors to prevent data losses, and integrating new sensing modalities. In this paper, we present Proteus, an easily managed infrastructure designed to automate much of the work in deploying and operating such systems. Proteus includes: i) scalable, continuous deployment and update of devices with automatic bootstrapping; ii) automatic fault and error monitoring and recovery with watchdogs and LED feedback, and complementary edge and cloud storage backups; and iii) an easy-to-use data-agnostic pipeline for integrating new modalities. We demonstrate our system’s robustness through different sets of experiments: 3 sensor nodes running for 24 days sending data (17.3 Mbps aggregate rate), and 16 emulated sensors (92.8 Mbps 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. 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.
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- Award ID(s):
- 1951880
- PAR ID:
- 10536400
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400701269
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Location:
- Houston TX USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3584371.3613006
