The Toronto Police Service (TPS) is undergoing continuous improvement efforts to enhance confidence and strengthen ties with our society by providing access to open data for public safety in Toronto. The Service would like students to identify artificial intelligence and machine learning applications for the Break & Enter data* available on the Toronto Police Service’s Public Safety Data Portal (PSDP), in order to:

1) Investigate potential relationships between Break & Enters and other factors, such as temporal data (time of day, day of week), neighbourhood, demographics, tree coverage, etc.

2) Derive insights and patterns

3) Build predictive analytics models

4) Create hot-spot mapping of increasing volume B&E areas within the 140 neighbourhoods and identify commonalities in the premise types

5) Deliver a final report and/or presentation of recommendations

Leveraging other open data sets, such as 311, City of Toronto, or others to be identified by students, is recommended.

B&E Data can be found at http://data.torontopolice.on.ca/datasets/break-and-enter-2014-to-2019