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Interactive platform for exoplanet detection using the astronomical transit method and artificial intelligence.

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About the Project

In recent years, data collected by several space missions dedicated to the search for exoplanets have enabled the discovery of thousands of new planets outside our solar system. However, most of these exoplanets have been identified manually. Thanks to advances in artificial intelligence and machine learning (AI/ML), it is now possible to automatically analyze large volumes of data obtained by these missions to identify exoplanets more efficiently.

Modern Technologies

For the development of this platform, we are using a combination of modern languages and technologies: JavaScript, Python, HTML, CSS, Node.js, Pandas, Numpy, and Amazon Bedrock. These tools allow us to create a robust and interactive platform for exoplanet detection, integrating artificial intelligence and citizen science.

Educational Approach

Develop an artificial intelligence model capable of detecting exoplanets using the transit method, utilizing open data from the NASA Exoplanet Archive. The system must analyze light curves (stellar brightness variations over time) to identify patterns that indicate the possible presence of a planet orbiting a star.

Scientific Analysis

  • Period (koi_period): time between transits (days).
  • Epoch / Time0 (koi_time0bk): central instant of the transit (days). Useful for alignment.
  • Depth (koi_depth): fraction of light blocked (ppm or %).
  • Duration (koi_duration): total transit time (hours). Very useful along with the period.
  • Ingress/Egress (τ): entry/exit time (min/hrs). Useful to distinguish real transits from false positives.

Astronomical Transit Method

How we detect planets around other stars

01

Continuous Observation

We monitor the brightness of thousands of stars continuously

02

Transit Detection

We identify periodic drops in stellar brightness

03

AI Analysis

Intelligent algorithms distinguish planets from false positives

Graphical representation of the transit method

Our Team

Developed for the NASA Space Apps Challenge 2025

Project Leader

Coordination and Vision

Frontend Developer

User Experience

Data Scientist

AI Algorithms