Kourai Khryseai

Hackademy, Culiacan | Leveraging AI/ML for plastic marine debris

Argos Mission

High-Level Project Summary

The "Argos Mission" aims to monitor marine debris above and below the water of the oceans using Computer Vision. This powerful tool can be uploaded to a mechanical model for areas where satellite monitoring is not possible to understand how erosion affects the calculation of marine debris on the sea surface, report back and link it with the satellite image to attach this information to a digital map that give us a more accurate visual understanding of concentrations and understand the variables that are not usually counted, such as salinity and temperature, harm marine fauna.

Link to Project "Demo"

https://sangaselu.github.io/nasa-challenge-web/

Link to Final Project

https://gitlab.com/sangaselu/nasa-challenge-web

Detailed Project Description

"Argos Mission" used different technologies for the final project, including the use of cloud services such as Azure for the Computer Vision API and Custom Vision resource, as well as Tensor Flow, Flask, Python and JavaScript. Computer Aid Design software, such as Siemens NX, was also used to development of the mechanical model.

The "Argos Mission" has input data collected by the mechanical model, through an Arduino module, to connect and send data over the internet, as well as satellite images from NASA's Cyclone Global Navigation Satellite System (CYGNSS). Both sources of information must be read by the Computer Vision model in order to develop the map found on our website.

The benefit of being able to observe underwater will help to understand the real amount of pollution in the seas, as well as the level of garbage to which the marine fauna is exposed and which ultimately feeds on it to survive. It is expected to have a visualization of water temperature in the ocean to determine the areas most prone to plastic fragmentation and increase the level of pollution of the seafloor, preventing species to coexist in these areas and affect the natural cycle.

Space Agency Data

NASA's Cyclone Global Navigation Satellite System (CYGNSS) information was used for the development of the map.

Hackathon Journey

The team said about the experience:

Mayra: It was very interesting, since I've never been so concentrated for so long in an exhaustive research about something in specific. At the same time, it was fun to plan so many different solutions to a problem and harder to choose the most adequate answer.

Evelyn: For me, it was a fun but stressful experience, but I learned to work better in a team and I also learned that it is possible to build a website in 10 hours and I will do it again.

Sofia: This experience was something completely new for me, but it is definitely something that everyone should do at least once in their lives, it is something that teaches you to work as a team in a better way, challenges you to think faster, to think out of the box, to want to do something better, not only than the rest of the world, but something better than what you did previously, it drives you to want to achieve more, to give more of yourself.

Sandra : My experience was very good because I was able to get to know teamwork better and get to know each other better with all the members and be able to have synergy.

Carolina: It's definitely one of the "Live changing experiences", totally! It made you step out of your comfort zone, and look for different answers with the existent technology in such a small time frame. Everyone thinks different, and everyone has something to say, so you learn also from others and their perspectives in order to resolve the challenge.

We were inspired to choose this challenge because we all care and are interested in this subject! Besides, we're only newbies developing AI/Machine Learning modules, so it was an excellent challenge to prove ourselves.