CAMALIOT Project Launches Mobile App for Raw GNSS Data Collection through Crowdsourcing!

CAMALIOT “Application of Machine Learning Technology for GNSS IoT Data Fusion”, which began in March 2021, aims to integrate data from the Internet-of-things (IoT) devices, including smartphones, and traditional GNSS data sources to leverage Big Data, Data Fusion and Machine Learning (ML) technologies to unleash innovation opportunities in GNSS science fields. CAMALIOT is extending the current capabilities of the GNSS Science Support Centre (GSSC), with IoT-enabled GNSS data processing pipelines to support several use cases.

The consortium has developed an Android app (“the CAMALIOT app”) for the collection of raw GNSS data from smartphones. Taking advantage of dual frequency chipsets now available in some Android mobile phones, the Android app logs data from all available satellites. A crowdsourcing campaign, launched at the beginning of March 2022 and running for 4 months, will collect data through a citizen science approach. Citizens and interested GNSS researchers are encouraged to download the app and collect data by placing the phone on a window ledge, e.g., at night when the phone is static, and to then upload the data to the CAMALIOT server. The data will then be ingested into ML pipelines for determination of tropospheric parameters to support weather forecasts on Earth, and the second one concerning the monitoring of space weather, important for satellite operations and communication. Researchers interested in using the raw GNSS data collected through the phone can download the data in RINEX3 format.

The CAMALIOT mobile app is available from the Google Play Store or via the dedicated website: https://www.camaliot.org, which contains more information about how you can participate.

More information on ESA’s website