Inspiration
With rising crime rates and the ever-increasing housing prices in Los Angeles, it is getting more difficult to find a safe and affordable place to stay in LA. Hence, we developed SaferLA, a web app to help people find out how safe a neighbourhood in LA is and how much it cost to live there.
What it does
SaferLA allows users to input a geographic location/address for the desired housing accommodation. Our web app will display the median rent price and a general risk level of the area based on the past decade’s housing and crime statistics.
How we built it
Back-end Development: Python Flask + Machine Learning Algorithms (Classification and Regression Models) for prediction (Based on housing and crime data from www.data.LAcity.com) Front-end Development: HTML, CSS, and React.js + Google Maps API integration Deployed on Google Cloud Platform
Challenges we ran into
- Slow Wi-fi throughout the event makes it hard to hack efficiently at times ☹
- Integrating API and connecting front end to back end using Python Flask
- Our model had a hard time to output the correct results
- Had a hard time parsing online data and training the ML model for prediction
Accomplishments that we're proud of
Implementing a web app that is built on Google Cloud Platform!!! Successfully integrating Google Map API which allows to auto-complete the location input and show the location on a map. We are proud of creating a web app that outputs the correct result and has a nice UI.
What we learned
- Set up servers and utilize Google Cloud Platform, Python Flask, and APIs
- Use HTML, CSS, and JavaScript to create a simple and concise web app
- Apply Machine Learning Models
- Implement Google Map API
What's next for SaferLA
- Include more features or parameters for better accuracy and prediction
- Expand the scope of our app outside of LA
Built With
- css3
- flask
- gcp
- google-maps
- html5
- javascript
- keras
- lacity-data
- python
- react
- tensorflow
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