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ECOBOT

CHALLENGE SELECTED :

LEVERAGING AI/ML FOR PLASTIC MARINE DEBRIS CHALLENGE

TEAM MEMBERS

  • Zeinab Essam Elgohary
  • Mostafa Hamdy
  • Rania Tarek sakr
  • Ahmed Gomaa Negm
  • Amr Basha

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It is believed that at least eight million tons of plastic end up in our oceans every year and comprise 80% of all marine debris present—from surface waters down to deep-sea sediments. Our challenge is to leverage Artificial Intelligence/Machine Learning to monitor, detect, and quantify plastic pollution and increase our understanding about using these techniques for marine debris solution.

DESCRIBE YOUR SOLUTION

Our solution is based on the SWARM Intelligence that is the collective behavior of decentralized, self-organized systems, natural or artificial.

Our solution is mainly divided into

  • Practical model
  • ECOBOT GUI
  • MODEL
  • Output data visualization

And ECOBOT can operate in two cases:

  • SWARM Loose case

where there is no special environmental condition for the Swarm to operate in.

  • the SWAT CALL

the SWAT is activated only in case of natural disaster occurrence

DESCRIBE YOUR CHALLENGE

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PRACTICAL MODEL �

Razer Clear bot Design copy-Rights

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AI MODEL

ECOBOT workflow

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GUI

Tracking map

Swat screen

Disaster map

Sensor reading

Select mode screen

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VISUALIZATION

All Plastic debris

Plastic debris

Microplastic debris

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RESOURCES

  • GitHub link :

https://github.com/MostafaBoshta/EcoBot

  • Our site link:

https://sites.google.com/view/ecobot-gui/home