Google maps does not always provide the safest way to travel around the city. It does not consider the dangers that a busy urban area like NYC may have. WalkSafe NYC provides the safer approach to mapping your path from Point A to B.

What it does

Our project aims to help children travelling around NYC plan the safest walking routes. In this project, we considered possible dangers to avoid by utilizing datasets such as traffic accidents, fire department twitter updates and registered sexual offenders. Our software processes and displays data on google maps in the form of shapes and colours along the suggested paths to the final destination. The information displayed is easy to understand and provides ease of use for children to identify safety hazards.

How I built it

Utilizing the NYC traffic accident dataset, we performed unsupervised machine learning using k-means clustering to find collision hotspots within Manhattan, NYC. These collision hotspots are found by finding the density of collisions for each cluster mapped at their respective centroids. Application built on Flask server with Python, including Twitter and Google Maps API.

Challenges I ran into

Scraping pages where data was not available. Rate limited API's. Cleaning data

Accomplishments that I'm proud of

The Quick Mafs team was able to develop a quality product in the span of two days. Despite the challenges faced, We were incredibly proud of the team development experience gained from this weekend, and look forward to future opportunities in big data application development.

What I learned

Through this project, we learnt how to manipulate a large dataset and relay meaningful information to a target consumer. Our application utilizes a combination of data sources to provide additional safety for children travelling around downtown NYC.

What's next for WalkSafe NYC

WalkSafe NYC is far from its full potential. With additional features such as live path rerouting, security monitoring, view for parents, family accounts, including accessibility data, etc. Additionally we hope to expand our application into mobile platforms and additional city areas.

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