(Here is the documentation for my thesis project at NYU’s Interactive Telecommunications Program. PDF version here.)

Riding through Mountains of Data:
Visualizations of Cycling

Robert Carlsen
Interactive Telecommunications Program
Tisch School of the Arts
New York University

Abstract

This project attempts to describe the cycling experiences of several riders in New York City through a series of visualizations. Specifically, I am interested to discover if riders similar to myself share a common experience through which a sense of connection could be derived.

Cyclists were encouraged to record their travels using their personal mobile devices running Mobile Logger, a custom iPhone application.
Log data was uploaded by the application to an online database in near real-time during each ride. This data was analyzed and filtered to provide source material for the resulting visualizations and system “dashboard” at http://mobilelogger.robertcarlsen.net.

Keywords

Cycling, New York City, sensors, iPhone, visualization, mapping, tracking, logging, mobile, application, bicycle

(more…)

After several rounds of rejection, Mobile Logger has been accepted and is available on the App Store! Feel free to try it out; hopefully some folks will find it useful. The source code for the application has been released under the GPL and is available on github.

I’m still actively recruiting participants for my ongoing thesis project, which involves visualizing cyclists in New York City. If you’d like your riding to become incorporated in some pretty pictures to be presented in May, then by all means start logging (and thank you in advance)!

Be warned, it’s a battery hog. Feel free to let me know if it gives you any trouble.

This is just a teaser for a project I’ve recently begun, but I had an “a-ha” moment when the visualization program finally came together just now and wanted to share…

This is geocoded accelerometer data from the handlebars of my bicycle on my commute from Greenpoint to ITP in the East Village. The sample at middle of the graph, and the red circle on the path coincide. I realized just now that this is a seam in the Williamsburg Bridge. Neat.

I’ll post proper documentation of the project as it becomes more robust…but I’m excited. Waiting for the heart rate monitor interface to arrive…looking to couple internal status with external events…

The TrafficFlow project has changed due to comments received during the first critique.

The table is circular with a smooth surface. User places an internet connected device on the table (mobile phone, PDA, laptop). After visiting the project’s website with the device and performing a brief initialization, particles representing internet traffic emanate from the device and begin to swarm off to the center of the table, where they become obscured in “the cloud”. As data flows into and out from the device, particles will flow between the cloud and the device. The movement of the particles will follow some type of fluid dynamics, tracking gracefully as the user moves their device. As the device is lifted from the table, the flow will cease.

Each particle represents packets of TCP/IP data. The particles will be color-coded by data type (web, e-mail, ftp, torrent, tcp overhead) and may be strung together to indicate groups of related packets in a data stream.

Methods:
Blob / Edge detection for devices on the table.
Packet Sniffing (Carnivore / libpcap) to watch network traffic / power visualization
Ajax web application to register users (associate IP with physical footprint of device)

System Diagram:
particle system visualization
projector (spec. TBD)
projection surface (allowing for rear projection)
camera with IR emitter (location of emitter TBD)
sensing (IR, WiFi traffic)

Procedural Direction:
1. user joins our public network
*. user places device on surface
*. user instructed to visit initialization site
4. site asks user to hit the connect button
5. site recognized users IP / UserAgent string
6. visual confirmation, ensuring the correct device is correlated with the IP
7. association is made
8. start sniffing packets
a. read packet header
b. determine source, destination, data type (as inferred by port number)
c. pass this data to visualization in the form of parameters
9. begin visualization
10. if blob of associated device is lost, the ajax interface asks the user if they wish to reconnect

Points of Failure:
– confusion for those connected to the internet via mobile data service (GPRS, Edge, 3G)
– simultaneous user logo
– inability to maintain tracking of devices

Designing buttons for mobile devices. Each button has to evoke a word from a provided list.

happy, angry, scared, fast, nervous, cute, dangerous, search, glamourous, full, skinny, noisy, painful, tiny, quiet, hot, cold, sexy, free, autumn, childish, breaking news (more…)

(this is an initial report for a longer post)

in conducting field research for the CycleSense bicycle proximity sensor i’m looking to gather data about actual proximity events while riding and to correlate these events with video documentation and personal annotation from the test subject…probably just me.

to that end, i’ve worked on rigging up a data logging solution for the sensor package. there was some information on using bluetooth enabled mobile phones as a storage device, communicating to a bluetooth module such the blueSMiRF attached to a microcontroller. in this case, an ultrasonic rangefinder is read by an Arduino which sends the range values through the blueSMiRF to a nokia phone. (more…)

I’ve been enamored with the RjDj iPhone application after Corey mentioned it on the list. At first I was turned off by the developers talk about it being a “digital drug” but got hooked when the documentation indicated that it was Pd (pure data) ported to the iPhone.

At the risk of providing a terrible description, Pd is a (free) visual programming language, (more…)