The Great Pacific Garbage Patch (GPGP) is the single-largest deposit of debris in the world, with a total area estimated to be larger than Texas. Within the GPGP, nylon fishing nets account for approximately 46% of the 79,000 metric tons of plastic waste. To combat this issue, using artificial intelligence imaging, an autonomous raft was prototyped to locate, pilot, and extract nylon fishing nets from the water. We built a catamaran-style raft with a pronged conveyor belt seated at the bow and an autonomous control and propulsion system at the stern. The conveyor belt collection method was an effective way to pick up debris from large bodies of water. With continued interest and testing from future MQP groups, this design will significantly decrease plastic waste within the GPGP.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Haboub, Khalil
• Kelley, Kaitlin
• Zimmerman, Eli
• Ghandour, Sakeena
• Spero, Lily
• Stevens, Shane
• Correa, Daniel
• Muirhead, John

Subject

• Computing
• Sustainability

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-042723-162603
• 106576

Parola chiave

• Ocean Plastic
• Nylon nets
• Computer Vision
• YOLO
• Autonomous Robot

Advisor

• Beck, Joseph E.
• Bertozzi, Nicholas
• Guceri, Selcuk

Year

• 2023

UN Sustainable Development Goals

• 6 - Clean Water and Sanitation

Date created

• 2023-04-27

Resource type

• Major Qualifying Project

Major

• Materials Science & Engineering
• Computer Science
• Mechanical Engineering
• Robotics Engineering

Source

• E-project-042723-162603

Rights statement

• In Copyright

Ultima modifica

• 2023-06-14