In January 2022, Toronto was hit by a record snowstorm of 55 cm over a period of 15 hours. This event was one of the top 10 of largest snowfall events for the city and resulted in $17 million dollars in City spending on winter maintenance operations.
The City’s snowstorm response received media coverage and negative feedback, prompting the City to invest in maintenance infrastructure and transparency of winter operations, including live maps which track snowplows and salt trucks during the winter months and servers to dispatch plow movement across social media platforms. As more snow storms followed in February 2022, three members in the Geomechanics Group, Thomas de Boer, Lucas Herzog Bromerchenkel and Ekaterina (Katia) Ossetchkina used this as an opportunity to do a deep dive on the City’s data, and answer questions about the City’s performance.
This work was done as the final deliverable in the graduate course CIV1498: Data Science for Engineers, taught by Professor Sebastian Goodfellow from the Geomechanics Group. The groups’ work, which used exploratory data analysis, sentiment analysis, REST server responses and GIS data manipulation, is available publicly here with a subset of the dataset, for other engineers to investigate and replicate: https://github.com/Plowing-Pandas-Toronto/Toronto_Snow_Plow_Analysis
The full article, from University of Toronto Engineering News, featuring this work is found at this link: https://news.engineering.utoronto.ca/u-of-t-engineering-students-dig-through-snowplow-data-to-measure-torontos-response-to-winter-storms/