LMC Studio

Seeing Like A Bike


How do you tell a city where to improve biking infrastructure? How do you get data to back your claims up? How do you convince people to participate in the study to collect data? What concerns with privacy would people have? If we know the causes of stress riders undergo, and the kinds of riders, we can define a user group, collect data about environmental factors that causes stress (and not physiological data, because it is subjective), and use those to form hypotheses and test them out.


From Prof. Chris LeDantec's prior research, we categorized riders into Fearless, Concerned, Worried and Non-users, based on Level of Traffic Stress (LTS). Then, the factors we concentrated on were physical environment (e.g. road quality, geography, air quality, noise), the social environment (e.g. traffic conditions, proximity to objects), and the rider (e.g. rider position and interaction with the bike). This combination of Digital Media, Physical Computing and IoT resulted in a large number of 'sensor boxes' that were deployed on bikes in Atlanta to collect data.

The Matrix IoT Platform
The Matrix IoT Platform on a Raspberry Pi, the "brains" of the system

Type Class project, collaborative Role Surface Quality Team sensor lead, Embedded system troubleshooting, Mechanical assembly, 3D modeling and printing, Server implementation Duration 5 months (Jan 2018 - May 2018) Tools Arduino, Raspberry Pi, Matrix, Sensors, Python Flask, Tableau, Autodesk Inventor, Dimension SST 3D printer Objectives System and Solution Architecture, Social Activism, Sensor interfacing, Embedded system networking, Sensemaking of contextual data, Ethics & Privacy



A major deliverable was the 'process book' that described our process in detail, explaining the alternatives we had considered, logic for chosing a particular method, list of equipment used, so on. It was, in essence, a recipe book if someone else wanted to build a similar system.


At the end of the class, we were able to build a fully functional prototype that attaches on a bike and collect data. In addition, we prototyped some enclosures and did preliminary data analysis to see if the data being collected made sense, and made a 'Process Book' explaining the choices we made and the steps to replicate our designs. The deliverables were well received and so far, we have not had any issues with our design (which is great, by design terms).

The following semester, Prof. LeDantec worked with other students to make the design more rugged and compact to go on bikes, and built several kits for distribution. Currently, the PIs are seeking more funding for effort, and looking for volunteers to ride roadways in order to provide the project with data.

Matrix new case
New casing for the Matrix
rugged box
More rugged box for sensors
box inside
Sensors packed into the box