Snowbound

Members

• Amanda Tuttle
• Daniel Heck
• Jaden Johnson
• Joe Lathrop

Abstract:

Snowbound Solutions is one of a few companies in the world which provide services to detect avalanches and notify subscribers in real-time. At any given site with Snowbound technology, a network of seismic data logging arrays use infrasound technology to analyze the environment, and determine when there is an active avalanche. These data loggers used to send data packets through a long and expensive path before the real-time data could be displayed on the web.

Our project aims to use the existing data loggers and interface with them to stream data. Once this data stream is established, ObsPy is used to read the binary data and convert the data to a format usable by their API.

Project Description:

Using the data cube we are able to stream binary data to the console. The binary data is in a propriotery format used by mSEED. mSEED is a way to standardize data so that it can be used to exchange and archive seismological time series data. In this case we are looking specifically for infrasound. We have a sample of the binary data below.

In order to convert the binary data to a format that is used in the client's API, we use a Python framework called ObsPy. Each second a cube will take 100 samples and create a trace as seen below. Inside each trace is the data that is sampled. As seen below as well.

Sample Traces:

Sample Data:

Using the data obtained from the data cube, we have implemented a basic graphing gui. This gui takes in a file as a command and parses the information and graphs the infrasound data.