RiskRouter-IM40

Problem Statement:

In large urban cities such as London, certain areas and streets can be more dangerous, especially at night time. While navigation apps are excellent in optimizing the fastest route with available transport options, they do not take into account the history and frequency of crime rates in certain areas which users should be aware of for their safety.

Proposed Solution:

We propose to analyse geographical crime rate data to identify areas and streets that would put people in a higher risk of becoming a victim of crime. The extracted data can then be used to plan safer routes during navigation or alert users of the potential dangers.

Target Audience:

Tourists and people that are new to the city and are unaware of areas that carry greater risk of crime.
Women and elderly who are at a higher risk of becoming victims of crime, and would like to know how safe their travel routes are.

Data sets:

Historical crime data (e.g. homicides, theft, pickpocketing) with as much detail on their locations as possible. We would reduce the scope of analysis to central London for this hackathon