Using a UAV and Edge Computing to Identify and Throw Away Trash
Open Access
Author:
Eden, Grant
Area of Honors:
Computer Engineering
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
Vijaykrishnan Narayanan, Thesis Supervisor John Morgan Sampson, Thesis Honors Advisor
Keywords:
UAV Drone Machine Learning Edge Computing Deep Learning
Abstract:
This thesis explores the application of edge computing on unmanned aircraft vehicle to
provide autonomous trash identification and disposal. The main focus is finding a way to run real
time object detection onboard the UAV without having to stream data to a remote server. Few
works explore the use of accelerators on drones to increase machine learning inference
computational speed. With this, this thesis explores the quantization of neural networks to
provide lightweight and accurate object detection models. This thesis also explores the creation of
an image set to train a model for trash detection, specifically plastic bags, plastic bottles, and
cans. The thesis demonstrates the application for autonomous, quick, and easy trash disposal via
drone and the potential for commercial use of drones for environmental cleanup.
