Abstract

Big data analysis of criminological-related datasets for Durham County Council.

Inspiration

The vast availability of multi-variate datasets that are contributors to possible crime attempts, inviting an attempt to plot, analyse and parse possible 'murder spots'. This can be integral in future decisions to identify possible risk-averse regions for further action.

What it does

Based on a number of factors, the big data algorithm parses areas deprived of common crime deterrent features, such as street lighting, CCTV coverage etc. A separate heat map of past crime attempt locations are also overlaid on the map.

How we built it

The optimal murder locations are determined by algorithmically processing and parsing data from the Durham County Council spatial dataset. Past crime attempts are provided using data by Police.uk criminology dataset.

Technologies

Python parsers for raw datasets, and for conversion from BNG co-ordinates to latitude and longitude. C++ algorithm to efficiently determine safety based on weighting from large geospatial input. JavaScript presentation of results using Google Maps API and powered by Google Cloud Services.

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