Google Cloud Platform: Data Sensing Lab @ Google I/O 2013

Posted on by Brandon Klein

This project is a partnership between the Google Cloud Platform Developer Relations team, the O'Reilly Data Sensing Lab and Device Cloud by Etherios.

Networked sensor technology is in the early stages of revolutionizing business logistics, city planning, and consumer products. We are looking forward to sharing the Data Sensing Lab with Google I/O attendees, because we want to show how using open hardware together with the Google Cloud Platform can make this technology accessible to anyone. The Software Google Cloud Platform, which provides the software backend for this project, has a variety of features for building applications that collect and process data from a large number of client devices - without having to spend time managing hardware or infrastructure. Google App Engine and its Datastore provide a scalable front end for collecting data from devices. Google Compute Engine is used to process and analyse data with software tools you may already be familiar with, such as R and Hadoop. Google BigQuery provides fast aggregate analysis of terabyte datasets. Finally, App Engine's web application framework is able to surface interactive visualizations to users.

The Data

All of the data collected by our sensor motes is open, and available as a public dataset in Google BigQuery. Data is is loaded into BigQuery from our real-time data stream at intervals during the conference. All users of Google BigQuery are provided with 100Gb of query processing per month free of charge. To run a query, use the following table designation: [data-sensing-lab:io_sensor_data.moscone_io13]

Example: SELECT * FROM [data-sensing-lab:io_sensor_data.moscone_io13] LIMIT 10