Shake Hack

Fall 2014 NuPIC Hackathon

• Colors map to anomaly score
  • Red: High anomaly score
  • Green: Low anomaly score
• Size of dot maps to magnitude
• 10 years of earthquake data (lat, long, magnitude) for the 1000km radius surrounding the Pinger, In. headquarters in San Jose, CA.
• Used coordinate encoder

See the video!

Requirements

• NuPIC
• Redis running locally
• Python, and dependencies
• Google Maps Javascript API Key

Usage

• Start redis

  $ redis-server

• Start run.py

  $ python run.py

• Start webapp

  $ cd webapp
  $ API_KEY=<insert API key here> python serve.py

• Open http://localhost:8080 in browser

TODO

This project is a work in progress. The initial mechanics of running data through NuPIC and presenting it to the user are there, but there's still much left to do to add value. Here's a sampling of some ideas:

• [ ] Create encoding scheme that better represents the magnitude of an earthquake event. Currently using the coordinate encoder as-is, mapping magnitude to radius one-to-one, but there's likely a better encoding scheme that takes into account the logarithmic scale of the magnitude. May also be some benefit to incorporating depth into the model.
• [ ] Make use of anomaly likelihood algorithm to classify events and/or incorporate additional traditional statistical models
• [ ] Automated cluster classification
• [ ] Additional user interactivity to explore events and replay periods of time
• [ ] Split data into training and test data based on variety of factors (bounding box, time, magnitude, etc.), save model on trained data set, load and replay new data
• [ ] Add a listener to http://earthquake.usgs.gov/earthquakes/feed/v1.0/geojson.php for real-time(ish) updates
• [ ] Display only a buffer of recent events rather than all accumulated. Maybe make the buffer size dynamic based on moving average.

Built With

• css
• javascript
• python