Recycle Sorter With AI
Broadcom MASTERS 2020

Project Summary
I
love to RECYCLE! Recently, I learned about a problem
called recycle contamination, where trash
contaminates recyclable items. Furthermore, different types of recyclables get
mixed. Sorting this
collection of recyclables is a significantly labor-intensive job in hazardous
work conditions and
prone to human error.
I questioned if Artificial Intelligence (AI) and robotics can be used to
detect and
categorize day-to-day waste items with high accuracy. If yes, then can a robot
perform physical
sorting of day-to-day waste instead of humans? What would be the accuracy of
this categorization?
Will the problem of recycle contamination be addressed such that recyclables are
recycled, making an
overall positive impact on the environment?
I collected hundreds of categorized images of various waste items and
used these to train
Google’s TensorFlow image classification AI model for six categories of waste.
Once I got the model
trained, I started my experiment by testing the AI with uncategorized day-to-day
waste items not
used in the training process and recorded the accuracy of the trained AI model's
image
classification. I achieved an overall accuracy of 87%.
Furthermore, I designed and built a recycle sorting robot with a
Raspberry Pi and Mindstorms
EV3 parts. When waste is placed on this robot, the robot detects it with the
help of a motion
detector and takes a picture of the waste. Then it uses my trained image
classification AI model
(the robot’s brain) to detect the type of waste it is and dumps the waste into
its respective
bin.
Project Board / Links
Awards
Broadcom MASTERS 2020 (National)
- Finalist (Top 30)
GSEF 2020 (State)
- Best in Category (Robotics & Intelligent Machines)
- Young Inventor’s Award (Patent Assistance)
- 2nd Honors
GASTC 2020 (State)
- 1st Place (Robotics Grade 5-6)
Cobb-Paulding Science Fair 2020 (Regional)
- 1st Honors
Cobb Tech Competition (NCTC) 2020 (Regional)
- 1st Place (Robotics Grade 5-6)