Mentor: Cameron Wallace
Project Room: ORCH 3072
Summary
As part of a study for the Port Authority of Vancouver, cargo ship positions reported by their navigation systems were considered. These discrete positions were pieced together into full ship routes which were then used to estimate the amount and distribution of pollution generated by cargo traffic through the port of Vancouver. In the original study, there was difficulty handling missing or erroneous position data. This project is to improve the reconstruction process of ship routes. Specifically, the problem is to look through the data to find all the records for a particular ship over a ten day period, and:
generate a route map for the ship over that ten day period;
identify when there is bad data for the ship and correct it so that the resulting route map is as close as possible to what it should be;
for bonus marks, make sure the routes don’t go over land (find open data to describe the coastline in polygons, and incorporate it).
Alternatively, identify characteristics that might flag “good” data vs. “bad” data (i.e. speed variations), and identify ways to systematically correct for bad data without minimum variation of the route. Identify the number of trips that would be caught and fixed with the methods.
About SNC-Lavalin
Founded in 1911, SNC-Lavalin is a global fully integrated professional services and project management company and a major player in the ownership of infrastructure. Our teams provide solutions in capital investment, consulting, design, engineering, construction, sustaining capital and operations and maintenance in many fields.