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Real-Time Cities: an Introduction to Urban Cybernetics Harvard Design School: SCI 0646900

Jason Lipshin Exercise #1: Case Studies in Sensing and Data Collection. Real-Time Cities: an Introduction to Urban Cybernetics Harvard Design School: SCI 0646900 Spring 2014. Environmental Sensing. Narrative Description:

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Real-Time Cities: an Introduction to Urban Cybernetics Harvard Design School: SCI 0646900

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  1. Jason Lipshin Exercise #1: Case Studies in Sensing and Data Collection Real-Time Cities: an Introduction to Urban Cybernetics Harvard Design School: SCI 0646900 Spring 2014

  2. Environmental Sensing Narrative Description: All of the projects that I chose deal in some way with environmental or bodily sensing. I tried to amass a collection that spoke to both the diverse methods for data collection (i.e. Galvanic skin sensors, air quality sensors, biological “sensors”, etc.) and diverse modes of actuating and communicating that data. 1 | Botanicalls 2 | Air Quality Egg 3 | One Tree 4 | Biomapping 5 | Tweet-a-Watt

  3. 1 | Botanicalls (Kati London, et al. NYU Interactive Telecommunications Program) Botanicalls opens a new channel of communication between plants and humans in an effort to promote successful inter-species understanding. Using a network of microcontrollers, as well as temperature, moisture, and CO2 sensors, plants that might otherwise be neglected are given the ability to call and text message people to request assistance. People who are unsure of their ability to effectively care for growing things are given visual and aural clues using common human methods of communication.For instance, Botanicalls will text its user when it is thirsty and will automatically post on Twitter if it feels that its human caretaker is being neglectful. URL: http://www.botanicalls.com/about/

  4. 1 | Botanicalls How was the data collected? Answer: CO2 sensors, temperature sensors, moisture sensors Why was the data collected? What is interesting about the data? Answer: The data was collected in order to create greater feedback loops of communication between plants and their human caretakers. What stories about the urban dynamics can the collected data tell? Answer: Users can gain valuable feedback on how well they are taking care of their plant. What sort of questions about urban dynamics can be answered by looking at the data? Answer: Although the information presented here is more individualized, the data could theoretically be aggregated and displayed on a map. Perhaps different neighborhoods could compare their relative strengths in taking care of their plants. How is the magnitude of the data is dealt with; limiting the collected data, limiting the dimensions in the data set, or abstracting the data? Answer: The data is mostly limited to individual patterns of care for a plant. However, by tweeting the data and potentially embarrassing the user, the project introduces a social dimension.

  5. 1 | Botanicalls How are particular patterns highlighted through techniques for tagging the data in order of their importance? Answer: Data is not filtered or ordered in any specific way, from my limited knowledge of the project. How does the original question to be addressed operate as the benchmark for eliminating unnecessary details in the data? Answer: The data is real-time and live streamed, and therefore operates as a continuous flow without elimination. Is the data of a static or dynamic nature? If dynamic, what is the frequency of change and what happens when it starts to change? Answer: The data collected from the plant is dynamic and real-time so thatuserscan see the immediate effect of their actions. The Botanicalls system only texts or tweets its user when its moisture level falls below a certain threshold, so it is difficult to pin down a consistent rate of change. Who is the target audience of the data presentation? Answer: Everyday plant owners, maker communities, digital art lovers. What are their goals when approaching the data presentation? What do they stand to learn? Answer: The data presentation operates according to mechanics of social pressure and individual self-regulation. The plants text when they are thirsty, and if they continue to go thirsty, they tweet about their owners, potentially embarrassing them.

  6. 2 | Air Quality Egg (Joe Saavedra et al. Parsons New School for Design) The Air Quality Egg is a sensor system designed to allow anyone to collect very high resolution readings of NO2 and CO concentrations outside of their home. These two gases are the most indicative elements related to urban air pollution that are sense-able by inexpensive, DIY sensors. If the amount of particulate matter sensed is above a certain threshold, an LED within the Air Quality Egg glows red. The data collected is also continuously uploaded to Pachube, a cloud service, where it is viewable as a timeline. URL: http://airqualityegg.com/

  7. 2 | Air Quality Egg How was the data collected? Answer: NO2, CO, and VOC sensors. An Arduinoand WiFi shield are embedded in a 3-D printed egg which are given to NYC elementary school kids and placed in their different neighborhoods. Why was the data collected? What is interesting about the data? Answer: The data was collected in order to learn more about the differing air quality in various neighborhoods within NYC. What stories about the urban dynamics can the collected data tell? Answer: Air quality within various city neighborhoods is dependent on a complex agglomeration of factors, including proximity to freeways and subway stations, oil drills, factories, socio-economic status, etc. When this data is mapped in aggregate, you can speculate on the factors which contributed to poor air quality. What sort of questions about urban dynamics can be answered by looking at the data? Answer: Hard conclusions cannot be drawn, but you can see correlations between air quality and the factors listed above when the AQ data is geolocated and placed on a map. How is the magnitude of the data is dealt with; limiting the collected data, limiting the dimensions in the data set, or abstracting the data? Answer: The data was initially collected by five classrooms of kids in NYC public schools. However, it then scaled up and went global, with AQ egg initiatives taking place across the US and Europe. When more data is available for a particular city, one would hope that the data becomes more accurate/granular.

  8. 2 | Air Quality Egg How are particular patterns highlighted through techniques for tagging the data in order of their importance? Answer: Having worked tangentially on this project, I know that outliers were often thrown out, as the sensors used were low-cost and not extremely accurate. How does the original question to be addressed operate as the benchmark for eliminating unnecessary details in the data? Answer: Initially, the students were putting their eggs both indoors and outdoors near their homes. However, this messed with the data, as indoor and outdoor air quality are very different animals and different conclusions can be made from the kinds of data collected. Is the data of a static or dynamic nature? If dynamic, what is the frequency of change and what happens when it starts to change? Answer: Data is definitely dynamic and generally real-time. The data is uploaded to an online, individual timeline via the site Pachube. This data is then transferred to the map visualization at the end of the day. Who is the target audience of the data presentation? Answer: NYC children and their parents, but also policy makers. What are their goals when approaching the data presentation? What do they stand to learn? Answer: I like that this project approached data presentation in a number of ways. The egg itself glows red when AQ is at dangerous levels. However, the data is also uploaded to an online cloud service where the social implications of the AQ data can beunderstoodwhen placed on an online map.

  9. 3 | One Tree (Natalie Jerimijenko, NYU Environmental Health Clinic) One Tree is one thousand tree(s), clones, micro-propogated in culture. Because the trees are genetically identical, in the subsequent years they will render the social and environmental differences to which they are exposed. The tree(s) slow and consistent growth will record the experiences and contingencies that each public site provides. They will become a networked instrument that maps the micro-climates of the Bay Area, connected not through the Internet, but through their biological material. There are also electronic components of the project which include Artificial Life (A-Life) trees that simulate the growth of the biological trees on your desktop. The growth rate of these simulated trees is controlled by a Carbon Dioxide (CO2)sensor meter placed near each tree. URL: http://www.nyu.edu/projects/xdesign/onetrees/description/index.html

  10. 3 | One Tree How was the data collected? Answer: Air quality data was collected by one thousand cloned trees in San Francisco. The trees register differences in the environment because they are genetically identical. Why was the data collected? What is interesting about the data? Answer: The data was collected to make a general statement about the importance of environment on health. The most interesting part about the data is its method of collection – a cloned tree de facto becomes a biological sensor. What stories about the urban dynamics can the collected data tell? Answer: One Tree tells the story of how the environment makes a difference and can be registered on the body. What sort of questions about urban dynamics can be answered by looking at the data? Answer: Generally, poorer neighborhoods will have lower air quality and this can be seen manifest in the general growth and health level of the cloned trees. How is the magnitude of the data is dealt with; limiting the collected data, limiting the dimensions in the data set, or abstracting the data? Answer: The “data collection” in this project is more fuzzy and is not focused on numbers which are concrete. Since it is an art project, it is more focused on contemplation and a novel means of collecting that data.

  11. 3|One Tree How are particular patterns highlighted through techniques for tagging the data in order of their importance? Answer: Again, patterns of inequality as manifested through the environment seems to be the main point of this art project. How does the original question to be addressed operate as the benchmark for eliminating unnecessary details in the data? Answer: It is difficult to tell which particular factors contribute to the growth or stunted growth of the cloned trees, so there isn’t much of a “filtering” process in this project. Is the data of a static or dynamic nature? If dynamic, what is the frequency of change and what happens when it starts to change? Answer: The project operates on very slow biological scales. Data is only legible after the trees have had time to grow. Who is the target audience of the data presentation? Answer: Artists, the general public, those who care about the environment. What are their goals when approaching the data presentation? What do they stand to learn? Answer: The data presentation is the most novel part of this project. The cloned tree in effect acts as a “data visualization” of air quality within the neighborhoods of San Francisco.

  12. 4 | Biomapping, Christian Nold (Royal College of Art – Interaction Design) Biomapping is a research project which explores new ways that we as individuals can make use of the information we can gather about our own bodies. Instead of security technologies that are designed to control our behavior, this project envisages new tools that allow people to selectively share and interpret their own bio data. How will our perceptions of our community and environment change when we become aware of our own and each others intimate body states? Using Galvanic Skin Response sensors attached to participants’ bodies, this project registered each participant’s emotional response to various neighborhoods within San Francisco (though the project was later tested in many cities around the world). URL: http://www.softhook.com/bio.htm

  13. 4| Biomapping How was the data collected? Answer: Project participants wear sensors which record their galvanic skin response (GSR), a simple indicator of emotional arousal, in response to their geographic location. Why was the data collected? What is interesting about the data? Answer: The data was collected to construct a map that visualizes wherecity dwellersas a community feel stressed and excited. What stories about the urban dynamics can the collected data tell? Answer: The data can be used to help people understand our collective/social responses to different neighborhoods within a city. What sort of questions about urban dynamics can be answered by looking at the data? Answer: Following the answer above, we might begin to ask questions about why certain neighborhoods make us feel anxious, excited, etc. How is the magnitude of the data is dealt with; limiting the collected data, limiting the dimensions in the data set, or abstracting the data? Answer: The magnitude of the data is dealt with by rendering it in a fuzzy/impressionistic way. The artist does not want to give the viewer hard numbers. He wants to create a general impression of the way people feel about the neighborhoods which they visit and inhabit.

  14. 4 | Biomapping How are particular patterns highlighted through techniques for tagging the data in order of their importance? Answer: This question is not explicitly dealt with in this project, but brightness of color and density of dots signifies a greater emotional response to a particular neighborhood. How does the original question to be addressed operate as the benchmark for eliminating unnecessary details in the data? Answer: The artist does not talk about his methods for data filtering, though I am sure the project participants were white, middle class, etc. So the data collected will reflect their biases, etc. Is the data of a static or dynamic nature? If dynamic, what is the frequency of change and what happens when it starts to change? Answer: The data is static, put on a printed out map. The lack of dynamism within the data presentation would be one of my key criticisms of the project – we have no sense of how perceptions of places might change over time. Who is the target audience of the data presentation? Answer: Artists and art lovers. What are their goals when approaching the data presentation? What do they stand to learn? Answer: The goal is to create an impressionistic view of inhabitants’ reactions to the city they live in. While most data viz projects focus on hard numbers, this project focuses on something harder to quantify – emotion and response.

  15. 5 | Tweet-a-Watt (Limor Fried, AdaFruit) Tweet-a-Watt is a device that monitors electricity and power consumption. Similar to Botanicalls, it creates social pressure by Tweeting your electricity usage to your friends, potentially embarassing the users into more sustainable habits. URL: http://www.ladyada.net/make/tweetawatt/

  16. 5| Tweet-a-Watt How was the data collected? Answer: A device that monitors electricity usage in watts which then communicates this information to the Internet wirelessly via X-Bee. Why was the data collected? What is interesting about the data? Answer: The data was collected in order to inform individual users about their electricity usage. The innovative part of the project is the way that this individual data is made social in order to create self-regulatory behavior in the user. What stories about the urban dynamics can the collected data tell? Answer: The data is more focused on individual power usage, but it could be made social by being placed on a map. What sort of questions about urban dynamics can be answered by looking at the data? Answer: Following the answer above, we might begin to ask questions about why certain neighborhoods use more electricity, etc. How is the magnitude of the data is dealt with; limiting the collected data, limiting the dimensions in the data set, or abstracting the data? Answer: The magnitude of the data is dealt with an a very individualistic way in order to change individual habits.

  17. 5 | Tweet-a-Watt How are particular patterns highlighted through techniques for tagging the data in order of their importance? Answer: This question is not explicitly dealt with in this project. How does the original question to be addressed operate as the benchmark for eliminating unnecessary details in the data? Answer: Data is collected in a continuous stream by the device, by I believe that it only Tweets once per day. Is the data of a static or dynamic nature? If dynamic, what is the frequency of change and what happens when it starts to change? Answer: The data is collected dynamically and in real-time, but it only reported via the Tweets only once per day. Who is the target audience of the data presentation? Answer: Environmentalists, DIY hackers and makers (the project has a huge presence in the Instructables community). What are their goals when approaching the data presentation? What do they stand to learn? Answer: The goal is to create self-regulation and reflection in the user. The social pressure aspect of posting electricity usage to Twitter is the most innovative part of this project.

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