A cloud-based ecosystem for predictive maintenance and management of shipping container

The shipping container is one of the most important assets of international shipping and global trade. Built to withstand extreme conditions, the quality of these large metallic boxes is often overestimated resulting in the international container fleet being perpetually undermaintained. As trade volumes increase terminal inspectors lave less time to conduct container quality inspections. This project aims to create an automated shipping container inspection system using high definition cameras and machine learning software. Each intern will be tasked with a specific part of the software development permitting them to apply their scholarly engineering learnings to solve real world heritage problems. By working in an office environment and being coached by learned researchers, they will transition from academia to the workplace organically. TO BE CONT’D

Faculty Supervisor:

Zheng Liu

Student:

Ran Zhang

Partner:

Canscan Softwares and Technologies Inc.

Discipline:

Engineering

Sector:

Automotive and transportation

University:

Program: