The Networked Street

This post is an assignment for my class  “The Urban Experience in the Networked Age”. It relates how I managed (or did not manage) to expose the layers of networks and data running through a particular street.

The  general goal of the exercise was to catalogue every object that sent or received data from or to the street. It sounded fairly simple, but it was not an easy task.

Broadway between 14th and 13th Street

I picked Broadway between 14th and 13th street as my object of study without knowing what I was getting myself into. The place seemed perfect for two hours of observation because  it seemed  to meet the requirements asked for:a semi-crowded space with a nice mixture of comercial (shops), economical (banks) and leisure-directed venues (cafe’s and cinemas).

View of the street from Union Square

Pen and camera in hand, I set up for the task.

I decided to start with  the intersection of 13th and Broadway (which seemed to be  the place where  the most amount of data was being exchanged).

Area 1 (Intersection):

Intersection 13th Street and Broadway (A: Pedestrian zone, B: Car zone)

Stoplights 13th/Broadway (#1 on map)

Pedestrian Lights (#2 on map)

Although the density of “networked” objects per meter seemed to be much more concentrated in the intersections, most of the objects I found there didn’t allow for a third party to feed on their data.

The best example of these type of objects are the pedestrian, traffic  and street lights run by the  NYC government. These objects are probably hardwired to a central operating center with highly-specialized technicians looking over it 24/7. (This is also applicable to Area 2 on the map, where practically the same traffic-oriented devices were found.).

I wrote my first personal note about 20 minutes after  I had started documenting these objects : “3:10pm, this is going to take  longer than I expected”.

Although opening the data of these objects  could weaken the security standards for the overal coordination of traffic in the city, it might also be very useful. One could create devices for blind people, for example, that could let them know when  it is safe for them to cross.

The problem of these lights is not only that the data for them can only accessed by one company, but that it often takes a specialist to understand what is going on behind . The only thing user-friendly about these devices is their immediate public function: to signal when to start and when to stop.( Red, yellow and green, the most basic data signals in city life. )

“3:15pm,  this is fun”

Pedestrian and Traffic Lights 13th Street (#1 and #2 on map)

While I was documenting these devices I noticed something flickering in the corner of my eye. I slowly turned around and found an LED screen from the Regal Cinema showcasing the names of the movies that were playing at that time. (#4 on the map)

I must say that, compared to the other government-owned devices, this privately-owned screen seemed to be much more dynamic and playful . It also seemed to be designed for easy  maneuvering of content (paying for a specialist  to actualize it every time a movie changes would be a waste of resources).Its control mechanism  should be pretty user-friendly.

However, the screen is not open sourced. If it were, one of the possible ways of using it would be to create community in that block.  One could send a community-oriented sms messages to a certain number, for example, and see the message bounced back at the passing crowd.

Regal Cinema LCD Screen (#4 on map)

Moving onward I found one of the most obvious data-producing/receiving objects of contemporary city life: the open Wifi network. In this case, it was the one owned by the Cosi café (WIFI name: Cosi) on the other side of the street.

The area covered by the WiFi signals seemed to cover both the traffic and pedestrian lights and could have even reach the privately owned screen in the other side of the street. (see #6 on map) A young woman, who seemed to be a student of art or design, was obviously using the WIFI to download things from the Internet. Her Mac was probably password protected, however the interfase that she used to share stuff was probably the most user-friendly device on the whole block. Imagine if she where linked to the streetlight or the cinema screen across the street! She could play around with this information in unlimited ways!

Cosi Cafe´s Wifi (#6 on map)

3:30pm: too many layers!

I took out my Iphone to get a sense of how many other Wifi signals were active in that space at that particular time.  It was then that I realized that everyone around me was using the phone while walking. Everyone, without an exception.

It was impossible for me to record this fact on the map, a more usefull device for a visualization of this data could be a camera that used a time-lapse shot to focus on the street from a building or a window. How could I, by myself,  make sense of all this amount of information that was being shared all around me? I feltlike the needle in the haystack, confused as to what my situation was in that hyper dense mayhem of signals.

3:45pm-note to self: “this is impossible, too many wifis, phones!”

From that moment on the feeling that I had lost my internal “compass”, so to speak, only grew stronger. The invisible worlds of data surrounding me exceeded comprehension.

This is the view that half the people on the street were seeing that day.

The sensation of being surrounded by streams of information finally became all encompassing: I saw people buzzing other people into their buildings through electrical signals; I became aware of how people in a bus stop reacted to the MTA bus that had an electric sign that said “Wall St” on it; I noticed how credit card owners use dthe Citybank ATMs to get money out of their account; I heard security alarms measuring the rate in which people came in and out of stores; I perceived car radios connecting wirelessly to an antenna in the other part of town; electric doors opening, watches beeping, etc. etc.


Feeling exhausted, I sat down in the of Union Square plaza.

I revised what I had written in my notebook. Although I had managed to catalogue  more than 15 outlets/inlets for data, I had the feeling that I had only touched on the tip of the Iceberg. The New York´s data landscape was dense, for sure.

It was then that I  wondered what result would this exercise have if performed in Mexico City? Of course it all depends on where in the city one performed  it. The exercise, however, seems relevant in that it  might help the urbanist gain a better sense of the type of people that are interacting in that neighborhood as well as what tools they use to communicate. In this sense, it could be used to implement public-technological policies that could be relevant to a particular form of (networked) life.

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