Avoid Collisions: Saving Life and Property in Space

High-Level Project Summary

With a mission to avoid any unfortunate day like 10 Feb 2009, when a US Iridium spacecraft was destroyed by a Russian defunct spacecraft due to an accidental collision, which further added more chunks of Debris.We are looking forward to using the real-time data from the satellite databases, estimate the debris object velocity, visualize orbit, and also help in predicting the position of that object on a future date and time. This would help in detecting and visualizing any future collisions by the precise and accurate calculations using Artificial Intelligence. It would assist many space professionals to plan their missions wisely and save their monetary and non-monetary resources in space

Link to Project "Demo"

Detailed Project Description

10 Feb 2009: A Day not to repeat!


A collision between debris and satellites or spacecraft leads to huge destruction in the overcrowded space environment, resulting in the creation of more debris chunks. This heavily impacts the space economy, as well as a potential threat to the resources being sent to space.

If a satellite is hit by even a small object with a size of 1cm, it might affect the hardware of the satellite, and agencies might have to send another million-dollar mission to repair the damage.


We have presented a visual representation of the result in LEO (Low Earth Orbit).

Future plans involve actual programming using Artificial intelligence and Machine learning.

As the functional web pages need some time in coding, we have presented a general primitive Front end developed site, and an AdobeXD file for animated simulation to give an idea of our project results, explaining the features and benefits of collision prediction.


Using this solution; a professional can:

Get real-time information of the Space Debris object's coordinates, speed, velocity, and other relevant attributes.

Visualize the orbit of the Space Debris object.

Predict the attributes of the object on any given date in the future, to detect if there is a chance of any possible collision with another debris object or a satellite.


Some of the resources to be used are CesiumJS, SatelliteJS, CelesTrak, Python, ML methods.

Dataset used: NEOSSAT satellite data (XML), SpaceTrack CDM file (Tiros 4 debris object)


Space Agency Data

https://www.nasa.gov/centers/hq/library/find/bibliographies/space_debris

The Nasa Library led to an in-depth understanding of the Space Debris and its adverse effects due to explosion, collision with nearby satellites, rockets, or even the ISS.


https://orbitaldebris.jsc.nasa.gov/photo-gallery/

The visual representation helped in demonstrating how over-populated the LEO is and think of a suitable solution to avoid collisions in the overcrowded space environment.


https://www.space-track.org/documents/New_CDM_format_KVN_example_NearEarth.txt

We used this data to visually represent our prediction for the object Tiros 4 in the future.


https://data.nasa.gov/browse?q=space%20debris&

This library helped in performing a Competitive Analysis for our idea.


https://orbitaldebris.jsc.nasa.gov/library/un_report_on_space_debris99.pdf

The report was an inclusive file giving some powerful insights on Space Debris and some relevant technologies.

Hackathon Journey

We did participate in Hackathons earlier, but this was a totally unique experience. Though we faced several challenges like shortage of time, understanding how to use information from the database, etc, we got to learn a lot.

One of the key takeaways from this hackathon was to choose the right team members, who reciprocate the same passion, dedication level as the leader.

Our team representative, Aisha proposed to work on the Space Debris challenge, as this was one of the most trending topics these days, given the fact Japan recently launched a mission to combat the debris.

We're grateful to the whole team of organizers, mentors, especially Mr.Yarab Mustafa, and Mrs.Raneem Faisal, who came to our rescue amidst the challenging time.

References

https://www.nasa.gov/centers/hq/library/find/bibliographies/space_debris


https://orbitaldebris.jsc.nasa.gov/photo-gallery/


https://www.space-track.org/documents/New_CDM_format_KVN_example_NearEarth.txt


https://data.nasa.gov/browse?q=space%20debris&


https://orbitaldebris.jsc.nasa.gov/library/un_report_on_space_debris99.pdf

Tags

#debris #prediction #visualisation #design #ai #ml

Global Judging

This project has been submitted for consideration during the Judging process.