Abstract
Littering is a significant environmental concern that causes significant damage to the natural ecosystem and contributes adversely to human health. Monitoring litter accumulation is currently labour-intensive and costly, often resulting in action being taken only once the environment has already become polluted. We contribute LIZARD, a novel pervasive sensing solution for detecting and monitoring plastics that is tailored to autonomous vehicles. LIZARD relies on an innovative sensing pipeline that combines thermal imaging and optical sensing. The intuition is to rely on thermal dissipation patterns to identify larger (macro) plastics and use optical sensing to sample area with the highest density of plastics to identify smaller (micro and meso) plastics. Ours is the first pervasive sensing solution that can detect micro plastics in the environment and be integrated into autonomous vehicles. Indeed, state-of-the-art solutions are either limited to laboratory analysis with special instruments or rely on manual observation without being able to identify the smallest plastics - which often are the most dangerous. We evaluate LIZARD through rigorous experiments that combine controlled laboratory settings and in-the-field measurements carried out in three real-world locations to evaluate LIZARD. Our results show that LIZARD can be used to detect plastics of different sizes with an accuracy of up to 80%. The performance depends on the diameter of the plastics, the background surface, and the luminosity of the environment. We also demonstrate that our solution can be easily integrated with ground drones, enabling (semi-)autonomous litter monitoring. Our work offers an innovative way to harness pervasive sensing to address an important global (environmental) sustainability challenge while paving the way toward improved monitoring of the accumulation of harmful plastic fragments in the environment.
Agustin Zuniga
Pervasive Data Science group
Dr. Agustin Zuniga works in the areas of pervasive data science and artificial intelligence of things, especially in low-cost sensing and intelligent sensing pipeline solutions.