This week I explored layering canvas elements to create an animation effect between multiple users. The animation is the outcome of multiple canvas drawings being sent out and received by all clients simultaneously.
After spelunking through spelunking a bit longer, I’ve started to make some connections that weren’t necessarily apparent from the start, and I’ve begun to follow some tangents that are taking me on some exciting pathways.
Spelunking is first and foremost an act of discovery, in an old sense. It’s an act that embodies learning through experience but at the risk of incarceration, injury, or even death. There are several varieties, each demanding its own specialized equipment, talents, and acuities. What I find most interesting in spelunking (not having spelunked … yet) is the way in which it exposes processes that are beyond our control or out of our sight; at a planetary scale, exposing tectonic mechanics or at an urban scale, shedding light on the infrastructure that sustains us.
Scale is an important part of it all. By embedding oneself below the surface of the planet or in the bowels of the city, human scale is reoriented in ways that it could not above the surface. Below the surface, we are reminded just how small we are. Below the surface, the world doesn’t accommodate us and the shape of our bodies. Below the surface, we can become something other than divine subjects. It’s not that we are rejoined with the ‘natural world’ but that we catch a glimpse of how we might fit into a system of unstable dynamics.
For instance, by exploring the sewers of New York, I can confront an enormous infrastructure that carries billions of gallons of sewage each day (see Radiolab’s Poop Train). The system is crucial to the health and functionality of the city and enables us to detach ourselves from our output. In the same way, that modern garbage disposal does the same thing; just send it off into the ether.
Enough of that. Another part of spelunking and exploring in general is the potential for real danger or repercussions. In the case of urban exploration, the danger lies at the intersection of urban chemical processes (deadly gases), geologic and weather events (rain and ground water swells), the legal system, and transportation to name a few. This week, I will be attending a meetUp for Cavers in the Lower East Side and I will be conducting an interview with Steve Duncan, and urban explorer.
These observations from research are helping me develop a lens through which to critically evaluate my project work. The primary guiding questions that I can ask myself:
How does this iteration expose connections to broader systems?
How does this design manage forces that seek to stop it’s implementation?
I’m moving forward with a couple concepts. One is development of the interior architectural spelunking elements. I’m interested in investigating how these elements can reorient the body’s relationship with built space and observing the kinds of questions that arise about usability, function, exclusion, safety, and aesthetics. [INSERT PHOTOS] The other concept that I would like to investigate more is the idea of developing prototypes for devices that enable urban explorers to more easily explore, document, share, and subvert danger. These could be simple sensor based devices that monitor water levels in distant sewer regions, or devices that provide counter-surveillance to watch for cops and trains.
A basic experiment using the socket.io module for nodejs.
Here is how it works.
1. A server is launched that serves out index.html and listens for circleClick events.
2. Index.html is served up to the client (the web browser)
3. The <canvas> in index.html is listening for mouseClick events. When it registers one, it uses socket.io’s emit function to send the click coordinates to the server.
4. The server registers a circleClick event and broadcasts the coordinates of that click to all the other clients
5. Each client receives the coordinates from the server via a socket.on(clickFromServer) event, and draws a new circle at that coordinate.
gitHub repo here.
Shortly after asking the question, I learned that an equally important question might be “What is it not?”, because it’s certainly not the same thing as “caving”. More on that later.
With a subject as unfamiliar to me as spelunking, I began by identifying a few questions that I need to answer:
What the hell is it?
Where does it happen?
What kind of equipment does it require?
Who does it?
From these questions I was able to generate a series of sub-questions and start to reveal interdependencies and outside connections. I will be focusing on several of these questions to serve as a genesis for my exploration.
Question 1: What does it feel like?
As an exercise, I will explore the phenomenology of spelunking through manufactured experiences and (hopefully) an authentic one. I have begun designing interior spelunking artifacts to be inserted into buildings that can help simulate the experience. How can this be done without violating the life-safety integrity of a building? Should caves be regulated? Werner Herzog’s Cave of Forgotten Dreams features the oldest cave paintings yet discovered and recalls a time when a large portion of the human population may have lived exclusively in caves. How have the regulations changed?
Question 2: How has spelunking been represented in popular culture?
When I think of Spelunking in popular culture, I have very few references handy. Cliffhanger isn’t really about spelunking, it’s about mountain climbing, but I seem to remember a few fight scenes that take place in a cave. Horror based science fiction fantasizes about cannibalistic subterranean humanoids. Jim Henson’s Fraggle Rock was a muppet based children’s show that took place deep under the Earth. What would a spelunking drama be like? How could it be performed on stage? I’d like to produce a short dramatic sketch about spelunking.
Question 3: What can spelunking teach us?
Aside from the exhilaration of terror and discovery, what can Spelunking teach us? What are researchers doing in caves? What is our military doing in caves? How can we forge a better understanding of our world by squeezing through the cracks and crevices of its bowels?
Question 4: Who does spelunking exclude? Who does it destroy?
Not everyone spelunks, it pervades complete popular consumption for a few reasons: not everyone has a cave nearby, not everyone can is able bodied enough to do it, not everyone can afford it. What does the spelunking demographic look like? What type of impact does spelunking have on the cave’s ecosystem? Is the cave a sterile wasteland to be exploited for enjoyment or does our leisure take a toll on a sensitive environment?
There are so many more questions that I have, but these are going to be the guiding questions as I go forward and prototype, interview, and adventure.
The above images show a snap shots of dock availability and bike availability throughout the CitiBike system. The image in magenta shows bike availability at 9:30pm on Tuesday. The image below it, in cyan, shows Dock Availability at 9:30pm on Tuesday. Finally, I composited the two images to show their relationship.
The image was generated with Processing, this is how it works:
I based my code on Dimitris Papanikolaou’s example sketch [insert gitHub link]. The Processing sketch took in JSON (from CitiBike’s website) and then parsed each JSON field into variables that Processing could work with. The variables (such as latitude, longitude and dock availability) were then passed to a Voronoi class (from Toxiclibs) to generate the cells. In the end, I overlaid an SVG that I made in Illustrator to give the data a little context. Below is the image without the SVG overlay.
gitHub repo is here.
The chat room is an interesting medium for storytelling. First, the audience is (in this case) anonymous, which means it can have any sort of absurd, vulgar, or irrelevant response to the story being told. Secondly, the audience is largely idle; many people sit in the chat room and treat it as a passive form of communication with other’s that share a similar interest. Third, the audience isn’t captive, it responds to elements of the story as it’s being told.
All of these things affect the pace, tone, and content of the story being told.
Since nothing too out of the ordinary happened to me this week, I decided to recount a paranormal experience that I had as a child, using a fairly populated World of Warcraft chatroom as my audience. After browsing dozens of sparsely populated IRC chats, the WoW chat was the first that I came across that had over twenty users present.
When I joined the chat, there was no activity. I decided to start telling my story, sentence by sentence over the course of the next twenty minutes.
I told the story of seeing a dead man in my bedroom as a small child. The man was decaying and had tattered clothes; he hung suspended from my blue metal bunk bed, a noose around his neck. His lower torso was missing and he dangled just a few inches clear of the carpeted floor. I mention the gory details because they stand out vividly in my memory, and the thing that puzzles me about this experience is that as a five year old child, I had no frame of reference for this kind of visual. The memory prompts me to ponder the nature of memories, their mutability and ultimately their trustworthiness. If I had no visual reference for this type of experience, is it possible that I have been retroactively augmenting this memory as I’ve grown older; adding acquired visuals to the mental scene? Or did I actual see a ghost?
After a few minutes of reciting my story, I got a response, one related to hentai manga (porn). A joke, it served as a segue into an actual response to my story. This threw me off a bit, and as I continued my story I considered my audience member and began to engage them as I told the remainder of the story. The responder, recounted the phenomena of physically visiting a place that they had seen in a dream and encouraged me to research paranormal activities.
The actual exchange was quite slow, a minute or so would pass between each exchange. This is likely because IRC is a passive type of live communication; users are doing other things while being engaged in the chatroom. Because of this lack of immediacy, I was able to craft my story a little more thoughtfully than I would have been able to if I was speaking in person; a kind of self editing and authorial image management.
In ME++ Mitchell talks about “electronic nervous systems” of intelligent urban environments. Discuss an example of an intelligent urban system you are familiar with and discuss the elements of the feedback loop, how its form of governance works, and who are its stakeholders (goals, decision makers, evaluators, etc.).
The concept of an intelligent urban system is quite broad, varied, and encompasses many types of systems; cctv, mass transit, emergency response, private security systems, community websites, delivery and couriers, government, infrastructure, waste, roadways, etc. With such a variety of typologies intelligence quickly becomes a highly relative term. Of these systems, one in which I’m fairly familiar with is a private vehicle sharing program called ZipCar.
I have been using ZipCar for about six years now. It’s a relatively intelligent urban transportation system that provides a variety of vehicles for on-demand use. As a user, I reserve a car via a web or mobile interface. My account is linked to a credit card, and I am charged an annual membership fee as well as a per-hour usage fee for my time in the car. I do not pay for gas or insurance. I retrieve the car from one of many set locations, drive it, and return it to the same location within my allotted reservation window. The system is governed electronically through a combination of human-computer interfaces (me and my phone or web browser) and an RFID card reader that is mounted to the windshield of the car that will either grant or deny access to the vehicle. The intelligence largely lives in a database of users, reservations, vehicles, and locations. Gas is paid for by credit card that lives in the vehicle. When there are issues, a human is available via telephone to resolve the issues. I list these systems to highlight the conglomerate of systems that are tied into ZipCar’s operation; web enabled databases, radio frequencies, humans, global financial institutions providing credit, roadways, and architecture (in some cases).
The stakeholders in the systems are both private and public, but mostly private. Its primary goal, as a company is to make tons of money, and it has continually been heading in that direction as it aggressively expands to new markets. The public can be seen as a stakeholder in ZipCar’s system as well, if only in a minor way; there is an incentive to reducing the amount of cars in urban environments. A reduction means less space dedicated to idle vehicles.
Compare different models of sharing that exist (or you can think of) in MoD systems (e.g. vehicle sharing, parking sharing, ride sharing, etc.) What operation/control problems do they have? What would the ideal form of sharing be for you and how would its resources be controlled?
The single largest operation and control problem that MoD systems have is resource management and system balancing. I believe that in a large part this is due to the fact that their systems exists in much larger ecosystem of systems as well as human demands influenced by environmental constraints.
For instance, with a car sharing system like ZipCar, the reliability of the system is variable and based on factors such as traffic, human error, mechanical failure, and maintenance. One advantage that a system like ZipCar has over other systems is that the resource (the car) is always returned to it’s origin which means relatively little rebalancing of the system. The system also has variable rates; weekends are more expensive to drive due to high demand, and more spacious or luxurious vehicles carry a higher hourly rate.
Bike share systems are faced with much larger problems due the way the resources are used. Bikes are generally used asymmetrically, meaning they aren’t always returned to their point of origin. There is also a flat fee for use (with the exception of overtime penalties) which means that incentivizing the system for self-balancing becomes a difficult feat. There have been countless times when I’ve used a bike off-peak and spent up to a half hour trying to find an available (or functional) bike or an empty dock, which dissuades me from using the system all together.
The ideal system for me is a bike share that takes a few lessons from ZipCar. ZipCar doesn’t share quite the same system stress as a bike share, but it’s still there; there are peak usage times when it is maddeningly difficult to find a vehicle within a reasonable distance. However, I believe having a variable pricing structure opens up zipcar to incentivizing itself to regulate its system. If a bike share like CitiBike could adjust itself and its pricing structure or form an alliance with local businesses to incentivize use, I think some of its operational stress would be reduced. For instance, if riders are prompted with a discount at a coffee shop or grocery store that is closer to a more balanced station, perhaps they will help regulate the system.
I chose to consider identity as a cumulative construction of the people we interact on a daily basis. The portrait rapidly becomes chaotic as the videos are activated.
Click the image below to go to the webpage.
In Rush Holt’s piece for Wired, he argues that within 10 years time, over half of all video that will be consumed, by the entire population of the world will be live.
I’m going with my gut, I don’t think so.
The argument goes something like this: given the explosion of bandwidth and high speed internet connections the everyday person will soon be able to live stream every little piece of their life, whenever they choose. This means it will be commonplace to stream something like little Timmy’s soccer game to Gramma and Grampa in Palm Springs. This is wonderful, and the capabilities will be here soon enough, but I doubt that the ubiquitous capability to live stream life will signal such a drastic shift in the way that the world (or for this argument let’s assume half of Americans) consumes video. Sure, there will be an increase of live streaming, but not nearly to the extent of Rush Holt’s prediction.
Here’s why I don’t think it will explode like Holt thinks it will: production quality and content. The primary tools we use to document and share our daily happenings lives in our pocket; the cell phone. Cell phone videos suck, and not just because of the cameras. Let’s imagine a scenario in which we’re going to live stream little Timmy’s big game. We could hold our cellphone, put it on a tripod, snap it to a drone, drive a crane to the soccer field, setup an array of cameras, or get as sophisticated as we would like. However, the more sophisticated the feed, the more equipment needed and less feasible the act becomes. Maybe the tripod is enough for Gramma and Grampa, but spontaneous on-the-fly footage of mom hold her iPhone 12 is more likely to give them motion sickness.
The second reason I won’t take Holts bet is because of content. Just because little Timmy’s game will be streamed, doesn’t mean that Gramma and Grampa are going to watch nothing else. I don’t think there are enough Timmys or compelling live content to replace over half of the current video media-sphere. Now don’t get me wrong, I welcome the live shift, I just don’t think it can replace our appetite for compelling narratives and highly polished pre-recorded content.
I think the single most exciting aspect of the live shift is the potential for citizen journalism. We’ve already seen how internet enabled media can affect a political movement, just imagine if the recent events in Ferguson were being live streamed through the eyes of a protester instead of a giant media conglomerate.
Saki, Dan, and I would like to discuss two proposals for analysis and simulation.
Analysis 1: How does the citiBike infrastructure interface with public transit systems?
We will study and analyze the relationship of citiBike stations with other mass transit nodes. Do riders use multiple systems in tandem? Are there financial incentives to compete or cooperate with other modes of mass transit? We will use our analysis to simulate and optimize station locations.
Analysis 2: Who is using the citiBike system?
We will study and analyze the users of the citiBike system. What user groups are habitual users? How do user identities inform the growth of the citiBike infrastructure? We will create a parametric simulation of the system growth.