an iPhone application records accelerometer data at anywhere from 1-40Hz (arbitrary rate) which is geocoded using core location (including heading, altitude, and location). every second the most recent sample is uploaded to a server running couchDB. after a ride, the full-resolution file can be e-mailed or uploaded to the server. for the proof-of-concept the data is being plotted on a dynamic Google Map.

in the immediate future i’ll be adding live updating of the map via ajax or some other web sumthin’ dot oh technology.

longer term is to build out similar applications for android and symbian (or maybe just j2me if it’s feasible). i’m also planning on getting back to the ardunio-based sensor packages which started the project.

I’m logging the acceleration forces at the handlebars of my bicycle while riding through New York City. The body has roughly three contact points with a bicycle, the hands at the handlebars, the “seat” at the saddle, and the feet at the pedals. The downward force of the rider’s weight and pedaling force and the upward forces of the bicycle rolling over uneven ground are distributed over these three points. I was interested to see just what kind of forces are “pushing back” that I may not be aware of, myself lost in the act of simply keeping the bicycle upright and safely navigating through traffic.

To contextualize the raw accelerometer data I also tracking GPS location and eventually geocoding the raw data in software. The bicycle sensors are being transmitted via Bluetooth to a mobile phone and the data is logged with a custom written (but now open-source!) python script. Below is the first draft of the visualization.

I intend to add more sensors to record internal forces to see if there is a physiological response (HR, GSR, breathing, pressure on contact points) to external factors such as speed, traffic / road / weather conditions, time-of-day etc.

Video demonstration of the initial visualization.

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…