Turn your Android phone into a space monitoring tool with the Camaliot app – The Indian Express

The Camaliot Android app will allow users to turn their smartphones into a tool for crowdfunded science. All you need in order to participate is a compatible Android phone with a working satellite navigation feature and the Camaliot app which can be downloaded from the Google Play Store. The app is compatible with more than 50 devices, according to the project’s website.
Camaliot is a project funded by the European Space Agency (ESA) and is led by ETH Zurich in collaboration with a team at ESA. The researchers will combine data from many users’ phones with other sources of data using machine learning for applications like weather forecasting.
Apart from helping scientists create new earth and space weather forecasting models, participants also stand the chance to win phones and Amazon vouchers. This four-month ‘citizen science’ campaign runs until the end of July.
“Global Navigation Satellite Systems (GNSS) such as Europe’s Galileo have revolutionized everyday life,” explained ESA navigation engineer Vicente Navarro in a press release. “And the precisely modulated signals continuously generated by the dozens of GNSS satellites in orbit are also proving a valuable resource for science, increasingly employed to study Earth’s atmosphere, oceans and surface environments. Our GNSS Science Support Centre was created to help support this trend.”
As signals from satellites reach Earth, they are modified by the amount of water vapour in the lower atmosphere. As they pass through this vapour and other irregular patches in the atmosphere, they undergo ‘scintillation’ or fading and delaying. Data about this scintillation can reveal insights about the Ionosphere, where the earth’s atmosphere meets space.
The combination of dual-band smartphone GPS receivers and Android’s support for raw GNSS data recording is what gave researchers the option to use smartphones for this data collection.
Data from smartphones can then be combined with data from the thousands of GNSS stations on the ground on Earth with machine learning models to seek out previously unseen patterns in both Earth and space weather.
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