Developing a waste segregation assistant (mobile application) for households in Ghana
Developing a waste segregation assistant (mobile application) for households in Ghana
Date
2021-05
item.page.datecreated
Authors
Quaye, Trixy Naa Momo
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
As the slowly continues to deteriorate, many organizations and
sovereign states are responsible for innovating sustainable measures to reduce the production of
harmful substances and repurpose materials by adding value to them. Ghana is a rapidly
developing country. With this development comes a large amount of waste production, the
majority of which ends up in the landfills, subsequently destroying the soil and releasing harmful
gases into the air due to its poor waste management infrastructure. This project focuses on using
deep learning and mobile application technology to take advantage of its massive privatized
informal waste collection sector to redirect waste from landfills to treatment plants, thereby
addressing specific Using transfer
learning with a pretrained Keras model, a waste classification model with a 91% test accuracy was
developed. This enabled the average household user to sort their waste visually. Results of the
classification analysis are shared with waste collectors and recyclers registered on the mobile
application to enable them to engage in the specialized collection. This approach would sensitize
household users on the amount of waste they generated daily and prevent the contamination of
waste items when transported to treatment plants because waste collectors would be collecting one
type of waste from different locations at once.
Description
Applied project submitted to the Department of Computer Science and Information Systems, Ashesi University, in partial fulfillment of Bachelor of Science degree in Management Information Systems, May 2021
item.page.type
Applied project
item.page.format
Keywords
waste separation