# Project export: Safe Route

This document was generated by HackStack to give an AI agent context about a hackathon project. Sections are labeled with their provenance; content marked as truncated was cut to keep this document small.

## Project metadata

- Hackathon: Cal Hacks 10.0
- Tagline: App fetching real-time crime data around UC Berkeley and predicting the probability of encountering crime at a place.
- Devpost: https://devpost.com/software/safe-route-odjaqy
- GitHub: not linked
- Demo: http://getsaferoute.netlify.app/
- Team: contributor stats unavailable

## Devpost submission (written by the team)

### Inspiration

UC Berkeley students often received emails about crimes happening around the area. However, it is not very useful to know whether any dangerous incident happens near them or not, as well as whether they are at higher or lower risks in certain areas.

### What it does

Thus, we developed this simple web app called Safe Route that displays crime information in the last three months around Berkeley city. The information is scraped from WarnMe emails sent to students. The app also allows users to report whether there is a dangerous incident near them. The new data would be visible to other users as well.

### How we built it

We used React and Google Map API for the front end and Flask for the back end. Our backend code is responsible for scraping WarnMe emails and extracting the coordinate address of each email about crime. The data will then be used by our front end to render places where there are crimes. We also add a visualization effect to give users a sense of which region is high-risk.

### Challenges we ran into

It was our first time attending a hackathon and building a full-stack app, so everything was challenging to some extent. React was more challenging as we just learned it when the Hackathon began. Programming the backend was also challenging in handling server errors. It took a lot of time to set our project up, fix bugs, and connect the front end with the back end. Also, due to the limited time and our unfamiliarity with the tech stack, we were not able to add more complicated features.

### Accomplishments we're proud of

However, we were proud that we overcame most of the challenges during the development of our project, which took us hours just to fix just a few lines of code. We are happy that we powered through two sleepless nights and came up with a product that met our expectations.

### What we learned

We learned how to collaborate via GitHub. We also learned the basics of React, Flask, Google Map APIs, and full-stack development in general. These skills would help us build future applications more confidently.

### What's next

We want to implement more sophisticated features such as allowing users to contact each other when they need a walking companion and real-time updates. We also plan to use MindsDB to predict the probability of catching a crime and give the user the safest route to their destination.

## README (from the GitHub repository)

No README available.

## Detected evidence (automated analysis)

No repository was indexed for this project. Claimed technologies below could not be checked against code.
- Flask (technology) — claimed on Devpost, not found in the code
- React (technology) — claimed on Devpost, not found in the code

## Codebase structure

No repository index available.

## Key source files

No repository index available; no source files included.