Use Case: Aquatic Litter Drones

Litter Assessment: Identify Floating Plastic for a Cleaner Future

AI-powered plastic litter counter: from drone footage to cleaner waters


The service provides an operational environment at the iMagine platform for the detection and quantification of plastic litter floating on the water surface. It allows users to ingest drone footage of their area of interest to get back an analysis of the presence and count of litter items. 

Aquatic Litter Monitoring system offers precise, AI-driven analysis for accurately assessing aquatic litter, enabling targeted pollution control.

The Aquatic Litter Monitoring system ensures consistent, standardized litter datasets by automating image processing, empowering efficient decision-making and environmental action.

Aquatic Litter Monitoring system’s user-friendly approach extends to citizen scientists, fostering widespread involvement and awareness for a cleaner aquatic environment.

Main Features

  • AI model and processing methodology available on the iMagine Marketplace
  • Users can download the docker image and adjust it to their specific settings 
  • The service utilises the OSCAR instance operated by iMagine as an inference service to invoke the model from an external application portal 
  • Possibility to use the service with minimal skills, resulting in lower usage barriers for potential users.
  • No authentication is required for DockerHub
  • Access to OSCAR on the iMagine AI Platform through the EGI Check-in service

Target Audiences and Benefits

Obtain data on the change in plastic waste composition over a certain period of time from collected image data

Get an analysis of the composition of plastic waste for their recorded data

Adjust the service and its individual components to specific needs and settings.

Larger areas can be monitored and examined

Gain an understanding of the composition of plastic waste in specific areas for which data is available. Measures can then be taken in response to this established knowledge.

After the adoption of certain policies to reduce plastic waste, the effectiveness can be checked and quantified by comparing the waste distribution before and after the policy is implemented.

Gain an understanding of litter composition in order to identify most present litter items.

Clean-up operations can be carried out more efficiently by better planning routes based on where plastic litter is most prevalent

The collected waste can be quantified in order to obtain information about its composition

Clean-up operations can be carried out more efficiently by better planning routes based on where plastic litter is most prevalent

Results of clean-up operations can be quantified to gain an understanding how much and what litter was collected.

Get Started

Discover the service on the iMagine AI Platform

Related Use Case

Aquatic Litter Drones

Mature use case led by DFKI