Cross-contamination of recycling occurs when items that cannot be recycled are placed in the same collection bins as items that can be recycled. Over the past 20 years, cross-contamination has become a tremendous problem for recycling centers across the country and the world as they have transitioned to single stream collection which requires individuals to determine if an item is recyclable.

At the North Carolina School of Science and Math (NCSSM) alone, we recycle 23.66 tons of single stream material each year. There is a great need for inexpensive solutions that will enable potential recyclers to easily discriminate between recyclables and non-recyclables.

How can you help?

In our project, we use image processing and machine learning algorithms to help discriminate between recyclable and non-recyclables at the site of collection and to predict the level of contamination of a single stream container. Our hope is that this app will help individuals to identify potential contaminants prior to throwing them in the recycling bin, and to learn to recycle more efficiently even without the app. At the institutional level, we hope to reduce cross-contamination to less than 5%, teach students about machine learning and AI tools, and also provide an inexpensive mobile solution that can be used broadly in our community. We will be working on this project throughout the school year and also in the summer as part of the Summer Research and Innovation Program.

You can help us by submitting images of recycling and contamination to help us build our image database. Please submit images from the categories listed below placed on a surface to this Google Form. The images can be in any orientation and can be handheld or placed on a surface.

  • Aluminium foil
  • Battery
  • Aluminium blister pack
  • Carded blister pack
  • Clear plastic bottle
  • Glass bottle
  • Other plastic bottle
  • Plastic bottle cap
  • Metal bottle cap
  • Broken glass
  • Aerosol
  • Drink can
  • Food Can
  • Corrugated carton
  • Drink carton
  • Egg carton
  • Meal carton
  • Pizza box
  • Toilet tube
  • Other carton
  • Cigarette
  • Paper cup
  • Disposable plastic cup
  • Foam cup
  • Glass cup
  • Other plastic cup
  • Food waste
  • Glass jar
  • Plastic lid
  • Metal lid



  • Normal paper
  • Tissues
  • Wrapping paper
  • Magazine paper
  • Paper bag
  • Garbage bag
  • Single-use plastic bag
  • Polypropylene (plastic) bag
  • Plastic film
  • Six pack rings
  • Crisp packet
  • Other plastic wrapper
  • Spread tub
  • Tupperware
  • Disposable food container
  • Foam food container
  • Other plastic container
  • Plastic gloves
  • Plastic utensils
  • Pop tab
  • Rope & strings
  • Scrap metal
  • Shoe
  • Squeezable tube
  • Plastic straw
  • Paper straw
  • Styrofoam piece
  • Other plastic
  • Unlabeled litter

Examples of Images are shown below:

The Sustainable Recycling Project in the News

NCSSM Team Named National WINNERS in Samsung Solve for Tomorrow Contest

A team of NCSSM students led by Instructor of Engineering Dr. Letitia Hubbard has been named one of five NATIONAL WINNERS in the Samsung Solve for Tomorrow competition. As a National Winner, the NCSSM Samsung Solve for Tomorrow Sustainable Recycling Team has been awarded $100,000 in Samsung technology for the school.

The students created an app that uses image processing and machine learning algorithms to help people separate recyclables and non-recyclables. An estimated 25% of recycling is contaminated by waste, making cross-contamination a tremendous problem for recycling centers across the country.

Dr. Hubbard says, "This award is only a small glimpse of what happens at NCSSM and definitely could not have happened without all of the support from the entire NCSSM community."

NCSSM team National Finalist in Samsung Solve for Tomorrow Contest

The NCSSM team is now one of only 20 national finalists from an original application pool of over 2000 entries! Dr. Hubbard, the advisor for this project, tells team members they should be very proud of the passion and work ethic that they have exhibited over the past few months. As National Finalists, the team guaranteed $50,000 in Samsung equipment for our school. Because of the COVID-19 pandemic, the final round, a pitch competition, has been postponed. Work on the project will continue as a Summer Research and Innovation project at NCSSM.

NCSSM team named state winner in Samsung Solve for Tomorrow Contest

NCSSM has been named one of two state winners, from thousands of entries nationwide, for the Samsung Solve for Tomorrow Contest. Our teacher-student team led by engineering instructor Letitia Hubbard is developing an app that will reduce recycling contamination by using AI and machine learning.

The Samsung contest encourages teachers and students to solve real-world issues in their community using STEM skills. NCSSM is among the nation’s 100 State Winners (representing all 50 states) and will receive $15,000 in technology for its achievement. The NCSSM team will continue to work on their project, including creating a three-minute video on their project development, in hopes of advancing to the National Finalist round. Keep up the great work! See student Jason Li on ABC11 News.

Text and Photo credit: NCSSM Communications

Durham Students Create Phone App that identifies Recyclable Items

♻️ Our #NCSSM state-winning Samsung Solve for Tomorrow team continues to work toward their goal of being named a #SamsungSolve finalist. "Recycling contamination is a huge problem," said Jason Li, a senior at #NCSSM. "Once recycling gets contaminated, you can't recycle that anymore. So that basically goes to waste." Together, Li and fellow student Dalia Segal-Miller helped lead a team of students on an "artificial intelligence" project. Their prototype phone app uses #ai to quickly identify recyclable items and avoid contamination.

Watch and learn more!

Text and Photo Credit: NCSSM Communications

Best & Brightest: Not all Recycling is Created Equal

#NCSSM’s state-winning Samsung Solve for Tomorrow team was featured in WNCN's Best & Brightest! Our team, comprising 20 students and led by Engineering Instructor Letitia Hubbard, developed an app to reduce #recycling contamination through #ai & #machinelearning. “This is definitely a team and school-wide effort,” says Hubbard. Stay tuned in March for the voting portion of the contest! Watch the full feature here.

Text and Photo Credit: NCSSM Communications