SEAGULL: Low-Cost Pervasive Sensing for Monitoring and Analysing Underwater Plastics

We contribute SEAGULL, a novel pervasive sensing approach for monitoring and identifying underwater plastics. SEAGULL builds on an innovative light (LED) sensing solution that takes advantage of convolutional sparse coding to classify plastic debris according to their material (resin identification code). This enables SEAGULL to determine the composition of plastics in-situ, unlike existing plastic analysis methods which require taking the samples to a laboratory where they are analyzed using high precision measurement instruments. Through extensive experiments we demonstrate that SEAGULL correctly distinguishes between the main plastic categories (over 85% accuracy), is able to operate robustly against diverse water conditions (turbulence, turbidity, luminosity), and works with different sensing resolutions. We also demonstrate the practicality of SEAGULL by carrying out field tests in an ocean and a river, demonstrating that the performance of SEAGULL translates to real in-the-wild environments. Our work demonstrates how low-cost pervasive sensing solutions help to tackle environmental sustainability challenges, offering a new way to collect information about the extent and characteristics of underwater plastics and improving the scale at which monitoring can operate while overcoming the main constraints of existing techniques.