NYU Class Description & Syllabus

The Quantified Self About Town

Tues, 12:10pm to 3:05pm.
721 Broadway, NYC, Floor 4, Room 15

How can we take advantage of the connected technologies transforming individual data to massively larger scales in time and space? From smartphones to wearables, from social media to quantified self, the aggregation and geo-location of data is becoming a major part of how our spaces, cities, and regions are assessed and planned.

In this class, we’ll look at how we can design and deploy with some of the most commonly hackable instruments– microcontrollers, sensors, and phones– that collect environmental, social, biological, and personal data. Students will learn to access the computing and geo-visualization resources they need to deploy their own data collection instruments in the urban environment.

The class will kick off with findings from a January 2015 workshop at MIT called “Physical Computing and Urban Studies,” in which students will consider the political, historical, and social underpinnings of how sensors are used in urban studies and planning.

Student Prerequisites:
  • Interest in electronics and sensors. Experience in building and programming simple circuits is strongly recommended.
  • Please bring an Arduino Budget Pack (or equivalent components) to class.
  • Before the first class, please download Arduino and Processing. Additional software for class can be found in “optional supplies” below.

Class Format

  • First part (60-90 minutes): Lecture, discussion, critique.
  • Second part (90-120 minutes): Hands-on building & testing. Early sessions will offer technical how-tos and labs, later sessions will offer open work time for your projects.


  • Feb 3.
    • Introductions. HCI context, MIT workshop findings. Survey of sensors and tools.
  • Feb 10.
    • Lecture: Data journalism, by Al Shaw, ProPublica.
    • Hands-on: microcontrollers and sensors.
  • Feb 17.
    • Lecture: Satellite & in-situ data, by Lela Prashad, NiJeL.org.
    • Hands-on: data collection & spectral processing.
  • Feb 24.
    • Lecture: Transportation planning applications, by Jennifer Sta. Ines, NYC DOT.
    • Discussion of MindRider collaboration.
    • Hands-on: basic data analysis.
  • March 3
    • Lecture: Case study on tracking waste, by Kate Mytty, MIT DUSP & PSC.
    • Hands-on: iOS and mobile.
  • March 10
    • Finish up iOS lesson if needed.
    • Hands-on: Arduino GPS.
  • March 17: SPRING BREAK. 
    • Additional office hours as needed.
  • March 24: Midterm presentations.
    • Guest critics: Liz Barry, Public Lab; David Briggs, Blue Flame.
  • March 31;
    • Lecture: Traffic & appcessory paradigms, by Brian Langel, Dash & NYU CS.
    • Hands-on: Literature Review
  • April 7
    • Lecture: Crowd and open data, by Sarah Kauffman, NYU Wagner.
    • Hands-on: TileMill
  • April 14
    • Lecture: Social justice and ethical considerations, by Bex Hurwitz, MIT & RightsCon.
    • Hands-on: Persona design & user testing
  • April 21
    • Lecture: User experience design, by Colleen Kaman, IBM UX & smart cities.
    • Hands-on: continue persona design, user testing, & final touches.
  • April 28: Final presentations OUTSIDE!
    • Guest critics: JD Godchaux, NiJeL.org; Alyssa Wright, Mapzen.

Optional Supplies (to be discussed in first session)

Office Hours: Wednesday by appointment.

Grading: Pass/Fail. Working in groups is strongly encouraged.

  • 35% Midterm (see checklist here). Demonstration of prototype & 1-page written abstract.
  • 40% Final (see checklist here). Demonstration of prototype & 1-page written abstract.
  • 20% Class participation.
  • 5% Weekly project blog posts.
  • Encouraged extra credit options:
    • expanded blogging
    • video documentation
    • project web site
    • conference paper

Special Events / Invitation to Participate: