PENGUIN: Aquatic Plastic Pollution Sensing using AUVs

Huber Flores, Agustin Zuniga Corrales, Naser Hossein Motlagh, Mohan Liyanage, Monica Passananti, Sasu Tarkoma, Moustafa Youssef, Petteri Nurmi

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Underwater plastic pollution is a significant global concern, affecting everything from marine ecosystems to climate change and even human health. Currently, obtaining accurate information about aquatic plastic pollutants at high spatial and temporal resolution is difficult as existing methods are laborious (e.g., dive surveys), restricted to a subset of plastics (e.g., aerial imaging for floating debris), have limited resolution (e.g., beach surveys), or are unsuited for aquatic environments (e.g., wireless sensing or Fourier-transform infrared spectroscopy). We propose PENGUIN, a work-in-progress AUV-based solution for identifying and classifying aquatic plastic pollutants. PENGUIN has been designed as the first system that can both recognize pollutants and classify them according to specifics of the material. We present the overall design of PENGUIN, introducing the different components of the architecture, and presenting current status of development. We also present results of plastic classification experiments using optical sensing, demonstrating that simple PPG sensors provide a low-cost and energy-efficient solution for classifying different plastics. Our solution can easily monitor larger underwater areas than what current techniques offer while at the same time capturing a wider range of pollutants.
Original languageEnglish
Title of host publicationDroNet '20: Proceedings of the 6th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications
Publication dateJun 2020
Pages 1–6
Article number5
ISBN (Electronic)978-1-4503-8010-2
Publication statusPublished - Jun 2020
MoE publication typeA4 Article in conference proceedings
EventACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications - Toronto, Canada
Duration: 15 Jun 202015 Jun 2020
Conference number: 6

Fields of Science

  • 113 Computer and information sciences
  • 1172 Environmental sciences

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