Project Arc

Project Info

The Ogrelords thumbnail

Team Name

The Ogrelords

Team Members

1 member with an unpublished profile.

Project Description

Problem brief

Pollution is still a prevalent issue surrounding the seas and oceans of Australia. In order to help better the protection of the ecosystem, the ability to predict major flow of waste will help maximise the efficiency of waste removal.


A forecasting engine, which allows predictions for where rubbish will end up based on currents. Alongside the forecasting engine there will be an app which allows users to report rubbish when they are out on the water.

Who are we?

We are project ARC (Australian Rubbish Cleanup). Our mission is to protect Australia's Reefs and Marine Life by removing plastic from our Oceans. Our promise is to leave a Clean and Brighter future.

What we are going to do?

Our mission is to help protect Australia’s reefs and marine life by maximising the efficiency of waste removal in our oceans. We can only do so much with code, we need the Australian community to help out and we have strong motivations backing our proposal. We will strive to encourage both young and older generations to use our mobile app, which is an easy way for the community to help contribute to the protection of our marine life and provide a healthier, cleaner environment for future generations to experience.

What’s our vision for the future?

We want future Australian generations to witness the beauty that is our marine life. Our current proposal is just the first phase of our 3-phase project.

Phase 1: Our current proposal.
Phase 2: Add more data to the predictive solution.
Phase 3: Implementing AI to map the predictive solutions for us.

What data have we used?

The data that we found to be the most valuable to our cause and goals included three of the datasets available. These datasets include: OceanTemperatures, OceanMotionU, OceanMotionV. We have gathered the horizontal and vertical currents throughout the Tasman Sea from the motion datasets and combined the information with that of the ocean temperatures to effectively predict the movement of rubbish in the area. The information from temperature dataset was used to see if there was any correlation between the quantity of rubbish and the temperature of the water.

For future aspirations, we will investigate wider datasets that cater for information all around
Australia. This will inevitably include Queensland so we will be able to better cater for local communities and businesses. Another positive effect a wider dataset can provide is the ability to better determine patterns in the data. A better understanding of the current movements and properties will create a more effective and efficient app for the community to respond to.

Data Story

How does the data impact the story we are telling?

Using water current data we can predict where plastic rubbish is going to be and therefore intercept using sea bins. Additionally we can use data sets to show where Australia’s pollution locations in combination with storm water drains to predict where plastic is going to be.

See our story on Facebook

Credit to Authors used in Video

Our Team

Team Photo.

Evidence of Work



Team DataSets

Australia Ocean 3D Bluelink Forecast Data Sample

Description of Use This dataset captures a one-year period and is provided to support anyone wanting to better understand the model or how to work with this data.

Data Set

Challenge Entries

Exploring the Oceans

How can we use ocean data to better support decision making for how we use our oceans? What sort of information presentation could provide more effective understanding of ocean dynamics beneath the ocean surface over a period of time?

Go to Challenge | 9 teams have entered this challenge.

Science Data Challenge

How might we make discovering and understanding scientific data for a location possible?

Go to Challenge | 9 teams have entered this challenge.

Litter Challenge

How might we prevent littering of fast food packaging?

Go to Challenge | 16 teams have entered this challenge.

Bounty: Decision Support

How can we make it easy to use weather and ocean data to our advantage? (e.g. when should you lay concrete, or go out yachtting or picnicking?)

Go to Challenge | 24 teams have entered this challenge.