You are currently browsing the URTing NYC blog archives for September, 2010


Listen to these maps

Through a link on the DIY Mapping Blog that was part of the reading for the week I found this episode of This American Life on Mapping. It’s structured into five acts based on the five senses.  Consider checking it out… very poetic.  I love this radio show.


09-28-10: Paper Prototype Testing

In-Class:

Discussion of readings
Testing of Paper Prototypes
Reporting back, ideas for further iteration
URT database:  setting up a project;  file types; data imports

Homework:
Read: Carto-City, Urban Probes

Write up 1pg analysis of our testing session today: challenges, limitations, ideas for further development. Incorporate this into your existing design brief. Refine your paper prototype, and animate it to demo your interface, specifically as it relates to URT, not just Citizen Sensor.  Post on the class blog for review/critique next week.

Noisy Subway

Group Members: Ryan Oh and Jamie Kennedy

Statement:

Our research question compares the noise pollution for people who take the subway. The subway trains create loud, screeching noises as they go back and forth on the tracks, which can create noise pollution. It does not matter whether you are on or off the subway train; the screeching noise is very audible.

Our inquiry hopes to reveal an uncomfortable level of noise pollution. By measuring this information, we can inform people about the noise that they run into everyday. We can find out whether the public transportation in New York City is safe or not for people, especially kids, infants, elderly people, or people with disabilities that affect their ears.

 Problem:

We encountered a problem with loud music and subway announcements because the sensor reads them with the same decibel measurements as the noise created by the trains. Trevor Cox states one problem with decibel measurement is that it does not differentiate between “negative” or “positive” sounds. The noise level of children, a fountain, or a train could exceed guidelines.

Method:

We took some sensor readings of traffic noises and people talking above ground. Once inside the stations, we measured the noise levels inside the train as it traveled from Union Square station to Times Square station and outside the train as trains departed and arrived. 

Audience:

 Our audience is the people in New York City because they might care more about the subway’s noise pollution. They may already know about it but they do not think about how it can affect them negatively. The noise pollution may be more important to a person with a disability because it may harm them more than it may harm a person without disabilities.

 User Scenarios:

 Scenario 1: This person lives near Union Square and he always wakes up to traffic noise around Union Square. He lives in an apartment and he experiences loud traffic noise with lots of people talking before he enters the subway. He enters the subway station. While he recharges his MetroCard, he suddenly hears loud music from inside the station. He hears the two trains coming from downtown and uptown. He misses these trains because he recharged his MetroCard. Then he goes and waits for the subway. He hears train sounds on the other train platform. After he waits for five minutes, his train comes. He gets on the train and starts to hear noise as the train travels. After four stops, he gets off at Times Square station and leaves the train station. Before he goes to his company, he hears lots of traffic noise.

Scenario 2: He lives in East Village and he works near Union Square. He takes the train when he is late or tired because he usually walks to Union Square. When he walks to Union Square, he experiences lots of drilling noise from construction work at Cooper Square. As he reaches the intersection around Astor Place; a person tries to cross the street on a red light, when a car honks and the driver yells at this person. Even though he walks to work, he still experiences a lot of noise. After he leaves work, he is really tired and he decides to take the subway at Union Square. Outside of the Union Square station, he enjoys the loud music in the Union Square Park. After that, he enters the subway station and he hears more music in the station but it starts to bother him because of the contained space. After three minutes, he takes the 6 train and he hears noise inside of the train. After two stops, he gets off at Bleecker Street and returns home.

Scenario 3: He lives in the Financial District and wants to the Maker Fair in Queens. After he leaves his apartment, it is really quiet in the Financial District.  After this quiet area, he enters the subway where it is really loud.  He takes the 4 train from Fulton Street station and he will need to transfer trains once he gets to Times Square station.  After he gets off the 4 train, he walks down a level to get to the 7 train. When he gets off of the train at 111th Street, the train is above ground.  Then he walks to the Maker Fair. 

Personas:

Persona 1: A person takes the subway consistently. This person takes the subway from point A to point B and vice versa on a daily basis.

Persona 2: A person takes the subway inconsistently. This person may occasionally walk instead of taking the subway and may only take the subway three or four times a week.

Data Set:

http://a.parsons.edu/~kennj467/urtingnyc/sensordata.pdf

Precedents:

In 2006, researchers reported that noise levels on the New York City subway could exceed the guidelines of the World Health Organization and the United States Environmental Protection Agency.

 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2438596/

Decibel (Loudness) Comparison Chart:

 http://www.gcaudio.com/resources/howtos/loudness.html

The Healthy Way

The Healthy Way (THW)

Group: Janvi Mody and Simoni Bhansali

Statement: To create an interface that allows people with airborne illnesses to find the healthiest possible part of New York City at a specific time.

Problem: New York City is one of the unhealthiest cities in the world due to the constant influx of airborne pollutants from cars, construction sites, stressed out smokers, and much more. In this unhealthy city there are a certain number of people that need to follow a healthy lifestyle due to various illnesses. It is for these people that we have created an interface that allows them to continue their lives, in the healthiest possible way.

Method: Using the design for the sensor module we will add more sensors such as particulate matter and Carbon dioxide. Using this we will get data from different sites at various times during the day. This will then be fed into a database that can be accessed on mobile devices. This information will help our audience to find the healthiest place to exercise or the healthiest path to work in at different times during the day.

Audience: Health conscious walkers around the city. People with air borne illnesses that should stay away from certain matter. People who exercise in the city.

User Personas and Scenarios:

1.

Laura Patterson

Laura has Bronchitis, caused due to passive smoking and city dust. Everyday she walks to work and has to inhale all the pollutants in the air that augment her illness. She is forced to take a number of pills everyday due to this. THW can help her find the healthiest path from work to home. In the evenings, very often smokers conglomerate at different spots and THW would help Laura stay away from these locations and better her health.

2.

George West

George is a health nut. He is a gym instructor and everyday he goes for an hour-long jog around the city. THW can help him map the healthiest areas for him on different days. These change daily as construction work and such are temporary things that can make a certain area unhealthy for a short period of time. With THW George can be fit on the inside and the outside.

3.

Vanessa Christiano

Vanessa is six months pregnant with a baby girl. The doctor has advised her to stay away from very noisy/dusty areas, and car fumes. Vanessa uses THW to stay away from places restricted to her, as over exposure to this can cause defects in her baby. This will help her and her baby. After all it has been proven that mothers breast milk is food with the highest concentration of contaminants. By keeping away from polluted areas Vanessa is not only ensuring a healthy baby, but also perpetuating her good health.

Smoke Signals v.2

Smoke Signals Team: Pamela, Jessica, and me. This is our mashup post. This represents our progress over the weekend in multiple parts (with more to come.)

Problem and Goals
Our project addresses how smoking impacts people in the surrounding area. We’d like to provide the data we collect to smokers so they can see the affect their smoking has on the environment and those around them.

Audience
Our audience is both smokers and non-smokers. We’d like to use our data to confront those who smoke with the samples from their polluted environments. By doing this we can provide them with a better understanding of the negative impact of indoor smoking on their health or how the outdoor air quality is affected by smoking occurring in a specific area.

Others who would benefit from this kind of data would be family members and roommates who share a home with a smoker; people like the New School faculty, students and the security guards who are usually posted near building entrances.

User Personas & Scenarios

Scenario 1 : Joseph (Parsons Security Guard) and the Students
Joseph arrives at The New School for his security shift at 12pm. As he’s walking into to the building, a huge puff of smoke is blown into his face. Disgusted, he tries to wave the smoke away. He enters the building, sits down at the security desk and starts his shift in a bad mood. He does a Google search for devices that monitor air pollution, and comes across Smoke Signals. It’s relatively cheap, so he orders one. He wants to use the device to collect carbon monoxide readings from his work environment and present them to his boss. His boss works on the 5th floor, so he’s not constantly exposed to smoke. Joseph wants to share a link to the online interface for the data with his boss, so his boss can better understand how he’s being affected by the smoking. He hopes that the readings will prompt his boss to either ban smoking in front of the building, or redefine the area where people can smoke.

As a result of Joseph’s efforts to decrease the amount of carbon monoxide in his work environment, the school has put more restrictions on where people can smoke. The new rule is that people cannot smoke within 20 feet of an entrance to a New School building. Students have reacted to this new rule as if nothing has changed. They continue to smoke directly outside of the buildings. Joseph tries to ask the smokers to move away from the entrance and reminds them of the new rule. He is always met with indifference, so he goes to his boss to discuss how they can enforce the new smoking rule.

Joseph’s Data Set
This data set would include readings from inside the building near the security desk, as    well as from immediately outside of the building.


Scenario 2 : Lisa Lisa, Nurse
Lisa Lisa enjoys her job at the County Hospital, especially the clean air of her work environment. Unfortunately, the air in her home is not so clean. Her husband, a writer, works out of their home, and is a smoker. He tends to smoke while he’s working at his office desk, and also while watching TV in the living room. When Lisa Lisa arrives home, she’s always greeted by the smell of smoke. Determined to change her husband’s habit of smoking indoors, she purchases Smoke Signals. As soon as it’s delivered, she turns it on and begins collecting carbon monoxide readings from different areas in and around her home. Lisa Lisa thinks it’s great that Smoke Signals transmits the data she collects to a web interface. Her husband is always working at the computer, so it will be easy for him to view the data online. She hopes that in confronting her husband with the data she collects, he will be encouraged to take his smoking outside.

Lisa’s Data Set
This data set would include readings from each room of the house, as well as a few different locations outside of the house (e.g. backyard, front porch).

Lisa’s paper prototype (available for demo in class):

Download the pdf of a sample interface and data set for Lisa Lisa:


Scenario 3 : Manuel, Writer
After viewing the Smoke Signals data, Manuel feels badly about how his smoking is polluting his and Lisa Lisa’s home. Viewing the data on the web interface has made him realize just how far the smoke travels, and that it doesn’t just affect the area immediately around him. He would like to completely quit smoking, but he knows that will take some time. In the meanwhile, he’s decided to try to keep their home’s air cleaner by smoking outside.

We developed a prototype logo and name for users to interact with Citizen Sensor.

Learn More
A button with links on SHS (second-hand smoke) articles and news

Reaction in 2003 to smoking ban in NYC bars and restaurants. Hard to believe that happened almost 8 years ago and was so controversial.

The expansion of that ban, extending to public places like parks and beaches that is being considered currently:

“The Centers for Disease Control says there is no safe level of second hand smoke for minors. The laws in California and Oregon are the most stringent – drivers risk fines if they are caught smoking with anyone under the age of 18 in the car.”

Smoking ban on Tokyo’s streets (because cigarettes were too close to children’s face level.)

There is a lot of information available about smoking cessation. Our study is more concerned with confronting smokers with the damage they are doing to their friends, family, coworkers, the environment in an effort to affect a simple change in smoking pattern, rather than the ultimate goal of getting the smoker to quit smoking. This is about respect of others, and making baby steps towards curbing unhealthy behavior.

The relationship between SHS and adverse health. The flight attendant study.

Related Studies, Outdoor Tobacco Smoke Study

Dharavi

Following our discussion with Vyjayanthi Rao, and the discussion about Dharavi, I wanted to share this BBC project, which interviews various residents.

09/21/10: Urban Research / Citizen Sensor

In-Class

  • Urban Research – Vyjayanthi Rao (NSSR/Anthropology)
  • Review of Project Topics
  • URT Research – Shannon Mattern (Media Studies/Urban Media Archaeology)
  • Precedents: TenderNoise,  CrimeSpotting
  • URT Database & data sets – Rory Solomon

–> Reading: Urban Probes & Beyond Decibels;  Inspiration: DIY Maps & PrettyMaps

Homework:
Incorporating initial feedback on your research project, expand your research with the following:

  • Identify one existing data set that can provide a larger framework for understanding your target audience, related concern, or topic.  Gather information for importation into URT (pending set up).
  • Develop at least 2 personas and 3 different user scenarios that relate to your project. Each should be detailed enough to inform the development of a user interface.  One persona/scenarios should be a contributor, per the larger vision of ‘Citizen Sensor’.  Two scenarios should detail specific ways this information would be accessed.  What is the resolution?  What is the data set?  How much information is enough?  What is relevant to the user?  Make notes on about this.
  • Create a new blog post, for your full design brief.  Include your statement, problem, method, audience, precedents, data set and cited relevancies from the readings.   This should be collaboratively written amougst your group.
  • Develop paper prototypes for each scenario (3).  Use 8.5×11 paper and a sharpie.  You can focus on the web interface, or a mobile interface.  Create each screen as we would need to see it, here is an example paper prototype video.
  • Check out the Android/Sensor kits and gather more data for your projects.  Aim to gather a minimum of 60 sensor reads and 20 images/sounds. These are flexible guidelines, the point is to work towards gathering enough data to build a solid argument, which can be presented in a form that has meaning for the user.
  • Read Urban Probes: Encountering Our Emerging Urban Atmospheres & Cox_CitySounds_Decibels_AcousticPlanning, and come to class prepared to discuss the relevance of both to your projects.

URT_notes week 4

09/14/10: Pecha Kuchas, User Experience

In-Class:
Pecha Kuchas – introductions & maps
Citizen Sensor – initial project ideas, small groups
User Experience Primer – Donna Linchow

Homework:

  • Pair up with at least one other person in class
  • Email us who you are partnering with (sooner is better)
  • Refine your research question, considering a specific audience
  • Write up a design brief to articulate your question, your initial research & some paper prototypes, with at least two personas/user scenarios, any precedents for visualization or topic.  What does your inquiry hope to reveal?  Who might care more or less about it?  What other data might further illuminate your argument?  Consider framing multiple perspectives for a shared question, as many of the suggested topics can offer very different user experiences.
  • Post this on our class blog by Monday AM, so our guests next week can read these
  • Gather at least 20 data entries, combining sensor data points with visual (photo) and descriptive data (see notes below)
  • Take some pictures of your groups as you are taking your sensor reads – both far away & close up, as process documentation

URT_notes week 3

9/7: Intro to Citizen Sensor

Thank you to Joe and Rory for opening up this discussion.

Please post your assignment either as a link to your personal blog post or an uploaded document.  While we are resolving how to make the sensors available for everyone, feel free to imagine data sets or visit data resources to insert into your drafts for this week.

Jess and Jane will be back on Tuesday.

URT_notes week 2