Lab Data

Here are all the data we've collected during past Data Sensing Labs. Pull down the raw data and the mote locations maps to play with them yourself. If you discover anything, we'd love to know about it! Contact us using the email address at the bottom of the page.

To download CAD files for the sensor mote enclosures, and other resources for building your own mesh network of environmental sensors, see the DIY page.


Strata Santa Clara: February 2013

Floor Plans and Other Useful Information

Strata Santa Clara 2013 was held at the Santa Clara Convention Center in Santa Clara, CA. Here are some maps indicating the position of each sensor mote. Each mote was given a unique 8-character ID (which you'll find in the .csv files), but the maps use a sequential 2-digit numbers to indicate their locations. You can match location numbers to IDs using the third file here.

Sensor Mote Data


Strata New York: October 2012

Floor Plans and Other Useful Information

Strata New York 2012 was held at the New York Hilton Midtown in New York, NY. Here are some maps indicating the position of each sensor mote. Each mote was given a unique 8-character ID (which you'll find in the .csv files), but the maps use a sequential 2-digit numbers to indicate their locations. You can match location numbers to IDs using the third file here.

Sensor Mote Data

Here is a collection of files containing different kinds of information collected by the sensor motes (all of which were identical). You can pull down all the data together using the first file, or look at each type of sensor data separately.

NOTE: Motion data captures the start (1) and end (-1) of motion. The PIR data shows no motion detected (0) or motion detected (1). For most events, you'll see motion = 1, PIR transitions from 0 to 1, stays at 1 for the duration of the event, motion = -1, and then PIR drops to 0.

Some Rudimentary Graphs

These are some very basic graphs of each data type that may help give you an idea of what was happening. For some much more advanced (and lovely) visualizations, see the work that Periscopic did with this data.