Facilitating the recycling process of catalytic converters using computer vision

Catalytic converters used in car exhausts are effective means of reducing pollutant emissions from internal combustion engines under normal operating conditions. They contain precious metals which makes them attractive for recycling due to their metal value and also the sustainability of the demand for these metals. The price of Catalytic converters can be determined based on their models and the amount of metal that exist in them. Currently, the price estimation requires human experts to identify the model of catalytic converters and then query a database to find the amount of precious metals in the catalytic converter and then estimate the recycling price of the catalytic converters based on the daily value of the PGM metals. The objective of this project is to build an application that can automate the price estimation of catalytic converters for recycling. We will train a machine learning classifier model using computer vision and integrate it in a cross-platform mobile application.

Faculty Supervisor:

Yasaman Amannejad

Student:

Partner:

Big House Converters

Discipline:

Computer science

Sector:

Other services (except public administration)

University:

Mount Royal University

Program: