radar-base@kcl.ac.uk, radar-base@thehyve.nl KCL +44 (0)20 7848 0924; The Hyve +31 (0)61 169 6842

Open source license

All components are available as open source software under an Apache 2 license. Have a look at our RADAR-base GitHub repositories, Wiki and Slack to get started!

Live monitoring

RADAR-base enables near real time remote monitoring of participant’s actively and passively generated data. The data is collected via Android and iOS apps into a RADAR-base backend.

Scalable & Extensible

Built around Apache Kafka for scale. Modular architecture and plugins-based – simple to build connectors to integrate data from additional wearable devices and APIs.

Open data standards

Schematized data storage in AVRO format to enable interoperability. Store of large volumes of raw sensor data as well as structured aggregated data.

I am a ...


I want to know how my data is treated or how I can participate


I want to deploy the RADAR stack to get more insight in my patients.


I want to discover new insights from the data generated by RADAR studies


I want to contribute open-source code to the RADAR platform

We invite you to attend a free symposium on mobile health, wearables and the RADAR-base platform on the 7th...
Register here  https://github.com/RADAR-base/GSoC The RADAR-base team is running several Google Summer of Code projects, if you are interested in...
The RADAR-base platform has been identified for innovation recognition in the area of mHealth and wearable devices by the...
This is a step-by-step guide to the newly developed web based application to manually upload data to RADAR-base. This...
Introduction What is an App server? An App Server (short for Application Server) can have many different definitions and...

Cite RADAR-base: RADAR-base: An Open Source mHealth Platform for Collecting, Monitoring and Analyzing Data Using Sensors, Wearables, and Mobile Devices.
Ranjan Y, Rashid Z, Stewart C, Begale M, Verbeeck D, Boettcher S, Dobson R, Folarin A, The Hyve, RADAR-CNS Consortium. URL: https://mhealth.jmir.org/2019/8/e11734/ DOI: 10.2196/11734 PMID: 31373275