Sensor integration across multiple data source to inform first responders in the event of severe weather (e.g. excessive flooding)

What it does

Display social media event with accompanying analytics on 2D, interactive map.

How we built it

We used 2 disparate data sources: IBM Bluemix Twitter Insight data and USGS stream gauge data.

IBM Bluemix Twitter provides geolocated, temporal social media events with accompanying sentiment analysis based off of their natural language models.

USGS nationwide stream gauge data provides discharge rate and stream height.

OpenSensorHub (OSH) driver supports retrieval of data from any station in real time.

The overall goal is to integrate the two disparate datasets within OSH's server and to be able to access and visualize the data with two separate clients, Spectralink and OSH web client.

Challenges we ran into

IBM Blewmix availability, data munging and reviewing, "Josh... just... never mind...", data conversion, integration of results into Spectralink and OSH, and determining methods of data retrieval

Accomplishments that we're proud of

WaterML standard into OSH. Also, We didn't kill each other... that good right?...

What we learned

IBM Blewmix, OSH, WaterML Standard, Teamwork with cynical teammates... not really!, USGS and WaterML data support

What's next for FordTough

Improve OSH integration to various data source. E.g. Twitter and stream data

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