What Our Project Does:

Our project, named "MagFuse: Bridging Field Lines," currently leverages data from NASA's resource page to analyze magnetic reconnection (MR) events in space. Magnetic reconnection is a complex process where magnetic field lines merge, impacting space weather. Our program processes vector components of the interplanetary magnetic field (IMF) to detect and assess MR occurrences.

How It Works:

The program utilizes data from NASA's resource page and processes spacecraft-collected IMF data using HTML, CSS, and JavaScript. It employs Express.js for server-side functionality and is hosted on Render, so its accessible to the public. By identifying MR events, it enhances space weather prediction, benefiting both public and private entities. Users can access and interpret MR analysis results, helping them make informed decisions regarding space assets and infrastructure resilience.

Benefits:

Predictability: Improved space weather prediction allows users to prepare for and mitigate the impact of MR-related space weather events.

Future Potential:

In the future, we envision introducing machine learning to predict MR events with even greater accuracy. This advanced prediction capability will play a vital role in protecting infrastructure both on Earth and in space. By leveraging machine learning, we aim to enhance our ability to anticipate and mitigate the impact of MR-related events on critical infrastructure.

What We Hope to Achieve:

Our long-term goal is to provide a comprehensive and predictive analysis of magnetic reconnection for both public and private entities. By harnessing the power of machine learning, we aspire to contribute significantly to the safety and reliability of space assets, communication systems, and terrestrial power infrastructure.

Tools & Coding Languages Used:

Tools: Express.js, Render
Languages: HTML, CSS, JavaScript

Space Apps 2023

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