Inspiration

As college students living in the city, we enjoy visiting new restaurants but want to know which areas are safe and which are not.

What it does

This mobile app allows the user to make informed dining choices based on neighborhood safety and food ratings. The app displays the best rated restaurants near the user, color coded based on our safety ratings. Each restaurant is also associated with relevant details including safety statistics and its Yelp profile.

How we built it

Backend: Using a Flask (Python) framework, we developed a REST API that given a user's current coordinates, returns a JSON object containing relevant information about restaurants nearby including safety statistics of each restaurant. We made this possible by developing our own safety index for San Francisco neighborhoods by analyzing recent SFPD public crime records.

Frontend: Using React Native and the Apple Maps plugins, we display the restaurants and corresponding information with a sleek map interface.

Challenges we ran into

The main challenge we faced was determining the safety scores for each restaurant. To overcome this, we developed a safety score for each neighborhood in San Francisco by parsing through crime records using python scripts.

Accomplishments that we're proud of

We hope this app can have social implications as, helping college students, women, and the elderly. We are proud to have created a convenient, useful, insightful application to assist restaurant-goers in finding safe, good quality places to eat.

What we learned

Crime data and analytics are extremely relevant to people and implementing these data to provide useful services to users is essential in building a safer world.

What's next for LateNight

We aim to expand to other cities and areas, create more detailed displays (such as heat maps), and extend the reach of our application to more users.

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