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RADAR-IoT: An Open-Source, Interoperable, and Extensible IoT Gateway Framework for Health Research
RADAR-IoT: An Open-Source, Interoperable, and Extensible IoT Gateway Framework for Health Research
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RADAR-IoT: An Open-Source, Interoperable, and Extensible IoT Gateway Framework for Health Research
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RADAR-IoT: An Open-Source, Interoperable, and Extensible IoT Gateway Framework for Health Research
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RADAR-IoT: An Open-Source, Interoperable, and Extensible IoT Gateway Framework for Health Research
RADAR-IoT: An Open-Source, Interoperable, and Extensible IoT Gateway Framework for Health Research
Journal Article

RADAR-IoT: An Open-Source, Interoperable, and Extensible IoT Gateway Framework for Health Research

2024
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Overview
IoT sensors offer a wide range of sensing capabilities, many of which have potential health applications. Existing solutions for IoT in healthcare have notable limitations, such as closed-source, limited I/O protocols, limited cloud platform support, and missing specific functionality for health use cases. Developing an open-source internet of things (IoT) gateway solution that addresses these limitations and provides reliability, broad applicability, and utility is highly desirable. Combining a wide range of sensor data streams from IoT devices with ambulatory mHealth data would open up the potential to provide a detailed 360-degree view of the relationship between patient physiology, behavior, and environment. We have developed RADAR-IoT as an open-source IoT gateway framework, to harness this potential. It aims to connect multiple IoT devices at the edge, perform limited on-device data processing and analysis, and integrate with cloud-based mobile health platforms, such as RADAR-base, enabling real-time data processing. We also present a proof-of-concept data collection from this framework, using prototype hardware in two locations. The RADAR-IoT framework, combined with the RADAR-base mHealth platform, provides a comprehensive view of a user’s health and environment by integrating static IoT sensors and wearable devices. Despite its current limitations, it offers a promising open-source solution for health research, with potential applications in managing infection control, monitoring chronic pulmonary disorders, and assisting patients with impaired motor control or cognitive ability.