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Reference Application for data analysis of Masaya Volcano data using Flask, PredixPy, TimeSeries, Asset, UAA, and PredixUI

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Introduction

To test our ability to digitize the natural world and take the first step toward creating better predictive systems, GE embarked on an expedition to see how industrial big data and predictive analytics can inform communities about dangerous volcanic activity.

This repository is home to the source code, data, and documentation for the Digital Volcano. The App is a simple reference demonstrating the use of Predix Services to help you learn how to extend it. It is based on the data set collected from industrial sensors installed in the Masaya Volcano near Nicaragua's capital Managua.

Learn more about the project by taking the Digital Expedition and view the sample app.

Getting Started

See the Getting Started Guide for details. You will need to complete the following steps:

  • Sign up for a Free Predix Account (no credit card required)
  • Clone this repository
  • Run pip install predix (making sure you have python 2.7.10+ and pip 9.0.1+)
  • Run setup scripts
  • Deploy your app with cf push

The specifics on how to complete these steps can be found in the Getting Started Guide.

Volcano Data

To access the volcano data you have a few options.

  1. Use the Digital Volcano App for simple exploration.
  2. Use the Volcano API to make REST calls.
  3. Use the CSV files in the setup/data directory to import to your preferred data science tools.

Predix Services Used

The following services have Free trial plans sufficient to run this application.

Getting Help

If something didn't work as expected and you want help:

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Reference Application for data analysis of Masaya Volcano data using Flask, PredixPy, TimeSeries, Asset, UAA, and PredixUI

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