How Citizen Scientists are Monitoring Global Meteor Shower Activity with Machine Learning Open Source Research: Siddha Ganju at the OAE's 3rd Shaw-IAU Workshop
| Main Author: | Ganju, Siddha |
|---|---|
| Format: | Proceeding poster Journal |
| Bahasa: | eng |
| Terbitan: |
, 2021
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/6014504 |
Daftar Isi:
- Citizen scientists have automated the Cameras for Allsky Meteor Surveillance (CAMS) data network, so data is automatically downloaded from the cameras, prepped for triangulation, and analyzed. Additionally, an ML algorithm replicates the scientists thought process to sift through the video captured each night to identify meteor showers with results published on the NASA CAMS Meteor Shower Portal. The open source portal not only aids in effective communication of ideas and results to a diverse audience but is a useful interactive educational tool used to explore meteor shower activity from the previous night globally and encourages citizen scientists to develop an interest in space science. Learn how to reuse the open source code for your datasets and explore meteor showers!