Category: NTNM Turned-In Assignments

Assignment 4: Sensors

Before our class session, I was familiar with sensors but didn’t realize the array of functions they have. While browsing the website I tried to get an understanding of the categories of the sensors. I was really interested in the Biometrics, Sound, and Movement sensors. Originally I was going to use the Sound Detector sensor, which is binary indication of the presence of sound, and an analog representation of its amplitude, and started brainstorming a new function for it but I couldn’t think of anything that hasn’t been used before. Then I found the NeuroSky Mindwave sensor, which shows your brainwaves and can monitor your levels of attention and relaxation. For my story, I decided to utilize both sensors because I think both functions would be beneficial for this scenario.

Growing up, I always slept with the TV on and it became a habit until I got to college. I noticed that the noises I’d hear while sleeping affected what I’d dream about. I sometimes dreamed myself into cartoons or movies  that were playing on the TV while I was sleeping. I would use the Mindwave sensor to put on people while they are sleeping to monitor their dreams while using the Sound Detector sensor to record data of how the amplitude, frequency, and type of sound affects the person. I would play a list of a distinctive sounds such as a cartoon, nature/ ocean sounds, a wrestling match, a horror film scene, and etc and record the brain activity on how the individual reacts to it. Then when they wake up, make a report about what they remember from their dreams.

I think understanding what affects what you dream about will help understand what they mean and the presence of sound is a good place to start.

NeuroSky Mindwave – https://www.sparkfun.com/products/14455
Sound Detector – https://www.sparkfun.com/products/12642

Assignment 4 Sensor Journalism

I hadn’t really thought too much about sensor journalism prior to this class but now that I’ve read up on it a bit more I think its a really great way for journalists to gather and then write about data.

I found the Sun Sentinel case study to be the most interesting personally. By combining the speeding gun data with the tollbooth data and GPS unit they were able to find some incredible information. They found that between October 2010 and November 2011 police drive their cars more than 6,000 times above the speed limit and not only that but over 90mph. By using sensors and and data they were able to uncover this culture of recklessness in the police department. What’s also interesting is that they got the idea for the reporting technique from a reader. This kind of falls into the category of UGC and I think it is important that all journalists are open to different solutions to problems, even if it comes from the comments of an article.

I wasn’t able to find any specific sensor that was used for the Sun Sentinel story, but I was able to find a variety of Accelerometers like this one and this one that measure movement and speed like the equipment used to measure the speed of passing by cars in the case study.

This got me thinking about potential stories that could benefit from sensor journalism. As I was browsing for different sensors I came across the SparkFun Sound Detector Sensor. I had the idea of using it to see how much/to what extent noise and sound effects our sleep. The Sound Detector would measure the presence and amplitude of sound throughout the night. We would also measure the quality of sleep of an individual through a FitBit or sleeping app to see at what points their sleep is disturbed. The sensor would enable us to see if there is any correlation to loud sounds/obnoxious noises disrupting the quality of sleep. We could test this out in loud cities, apartments near construction sites, rooms facing the street versus not and see the effects of noise of ones sleep cycle and overall health.

Assignment 4- Sensor Journalism

The case I found most interesting was about USA Today’s “Ghost Factories” project. A study had been recently published on 430 old metal working factories that closed down, and it was believed they  left behind heavy metal poisons in surrounding neighborhoods. Families began moving into these areas and had no idea that the soil their children were playing in could be unsafe. Alison Young, a journalist for USA Today, knew that their investigation would require soil sampling, but she assumed it would have to be outsourced. It turns out the with the use of an X-Ray Fluorescence (XRF) analyzer, reporters could do some of the data collection themselves. This avoids the huge expense of outsourcing and also increases the amount of data they could collect for the same money. Thermo Fisher is a company that makes a leading line of XRF analyzers, which are used in the fields of environmental regulation, resource mining, and industrial production.

The cost to purchase the scanner would have been $41,000 per unit, but they were able to rent them for $2,250 per device, per month. Using the scanners, they found that there was “potentially dangerous lead levels in parts of all 21 neighborhoods examined across 13 states. They found that neighborhoods in Philadelphia had areas where children would play with lead concentrations of more than double the EPA’s limit. The main takeaway from this case was that although environmental testing was a known investigative method before, the ability for journalists to rent electronic, self-contained devices opened up many more opportunities.

I couldn’t find an XRF scanner on sparkfun, but there are many available on Thermo Fisher. This story and the many types of environmental sensors had me thinking of the possibilities to bring awareness to the public on the quality of their natural resources. Access to clean water has been a major issue, especially when it is pumped through lead pipes. Even without the issue of lead contamination, there are many factors that can affect the quality of tap water. Similarly to how the soil samples were collected, water can be tested in areas that are concerned about their water quality. On sparkfun, there are many different types of environmental sensors, such as this one, which measures air quality, and this one, which measures the acidity and basicity of liquids. I also found some sensors on other websites that provide more data about the water, like this one, which records conductivity, pH, ORP, dissolved oxygen, water level/pressure, salinity, total dissolved solids, resistivity, density, air and water temperature, and barometric pressure.

I decided to use the NeuroSky MindWave Mobile+ Sensor (https://www.sparkfun.com/products/14455) to do research on how people perceive the images that they see in the media. This device comes with games and programs that one can use but it also has a way for you to write your own programs specifically to what your needs may be.  I would write a program that could tell how the brain changes when it sees different images, allowing us to understand how people may react to perceived negative and positive images.

This particular research would be based on “negative” images depicting the Black community in the United States and “positive” images depicting the Black community in the United States. The reason for this research is to record the reactions in the brain of people when they see themselves portrayed in a particular way. This has theoretical grounding in framing, gatekeeping, political economy, uses and gratification and many other sociological theories about mass communication and media.

If we study this an conclude that there are differences in the way the brain reacts to certain images then we can start to break down why certain images of certain communities are seen more than others and what the larger societal payoff is. Conversely, if we look at the feedback about positive images and what the brain does when it sees those images, we can argue that there needs to be more diverse coverage of certain communities understanding what both negative and positive images can do to audiences and why certain segments of society would not want the positive images and continue to perpetuate certain storylines with the negative one.

In the case studies, I was intrigued by the usage of the sensors that they used. I used to work with Dina Capiello in Albany, NY and I worked at the Houston Chronicle before she got there. I am both familiar with her environmental work and the areas in Houston she covered. I liked how the sensors she used could be hung in the atmosphere to collect the data. For the oil spill case study, again I was familiar with the areas since I lived in southern Mississippi near the Gulf Coast at the time of the oil spill. I remember seeing the huge oil clumps gathered on the beach but this was months after it happened and we dared to venture to the beach. I liked how the journalists used the balloons and the small digital cameras to get into the areas that the officials did not want journalists to go. It was very clever.

Assigment 4: Sensor journalism to tell stories in Cuba

While reading all the multiples examples of sensor journalism, my mind was flying to all the infinite possibilities we have to tell our own stories. My main takeaway is that we can build our specific and local database about any kind of topics. Sometimes, most of this data is private or government protected, or maybe it takes too long to get access to them and we cannot understand exactly what the experts did. But if we do it from scratch with our own technology and methodology, we can assure a great result to tell a wonderful story that can change the point of view of many people.

For example, some of the stories of the towcenter were developing a narrative story based on data from local areas, related to local issues. Most of the stories were done with a lot of creativity and imagination. Besides, they mixed various techniques, not only the data acquisition through sensors, but they added context and they used traditional journalism techniques to bring to life amazing stories.

I was really impressed by the story about air pollution in Texas. The journalist used her own DIY process to get data about chemicals on the air in some neighborhoods near an important local industry. She only had some hypotheses and complains from people who live there, but all the public data the industry released was apparently in the correct range. However, she went deep to the data and realized that the methodology used by the industry could leave a gap about what is the real danger of the air where the people actually lived. She then started to develop her own method and got advice from experts too (besides she was an expert too). She made people from the community to get involved in the project too. In the end, she came up with amazing results and analysis and was thoughtful enough to say she understood that the investigation was good for journalism standards but not for science. Despite her results showed a harmful level of chemicals in the air, all of the results were correct for the Texas standard levels.

This incredible example showed how the impulse of a journalist and a community, helped by experts, turned on the alarms of air pollution and made politicians to take care of this issue too. The story inspired other journalists to do a similar approach to other stories.

For me, using sensors and this kind of technology to tell stories is a completely new way to see journalism and open my mind really much to all the different things I can do. Looking to some of the sensors in the sparkfun webpage, my imagination started to run about different issues in Cuba that I could investigate better and help people in small communities.

For example, noise contamination in Cuba is really common. There is even a law that prohibit to exceed a certain level of decibels. On the other hand, some private and government business exceed that quantity in some very centric neighborhood.  It is known that high level of noise can affect human health and provoke several conditions related to stress caused by noise. My project could use some sensors to measure the level of noise in a determined neighborhood affected by that and find out if it really exceeds the levels and during what time of the day. There are several options for audio sensors on the sparkfun webpage, but doing a quick research gave me even more specific and professional options to a lower price on Amazon, so I recommend to explore all the options before doing a methodology for our investigation.

By doing this, in association with specialists and the opinion of experts I could create a good investigative piece with all the data and make people realize the danger they are exposed to. Of course, this should be combined with other standard methods of journalism, maybe a podcast an a video that shows the actual level of noise that affects different families.

The most important lesson here for me is that we have to be open to the possibility to create our own dataset and contrast that information with official data. We can go deeper and create a better methodology to get the data. We can make people get involve and create amazing investigative pieces with the most accurate information. I can’t really wait to do it by my own!

Assignment 4: Sensor Journalism

I read about the Washington Post’s coverage of the ShotSpotter sensor array. This device is something that was placed in strategic locations around the Washington D.C. area that records sound and alerts the police if there is a sound that is similar to a gunshot. In theory, this would allow police to be on scene of a shooting quicker than if they had to wait for a 9-1-1 call from a witness.

The Washington Post used this array and its data in a more journalistic manner. The police used ShotSpotter as an alert system. Once they received an alarm that the device picked up gunfire, they would deploy an officer or officers to the scene and that would conclude their use of the technology. When doing a story, the Washington Post dug much deeper into ShotSpotter’s data. They used the data to present ethical and practical problems that could arise from using this technology. They ran the headline “39,000 Shooting Incidents in the District” to capture readers’ attention, forcing them to read the article to learn that this system yields many false positives. In a incredibly detailed story, the Post dug into all of the data and was able to create visual representations of the areas with the highest concentration of gun violence.

This case study got me thinking about how else journalists could use some sort of audio sensor to be the first on a news story and to also compile and create large data sets. As a journalism student, I have come to learn that traffic and traffic accidents are some of the most desired stories. I think a sensory array could be used to detect the tell-tale signs of traffic and to accurately predict how much of delay there is in a certain area.

This sensor would use the sounds of passing cars to calculate the average speed at which cars are passing it. In theory, this data could be sent to a news organization and they can accurately report exactly how long it is taking commuters to get from Point A to Point B. It could also alert reporters, and in theory police, to the sound of motor vehicle accidents.

Assignment 4 – Sensor Journalism

Jennifer Castro

Sensor journalism is something that I hadn’t thought much about before our class lecture this past week. A lot of measurements and pieces of equipment fall into the sensor journalism subject that I hadn’t made the connection between either. The case studies I read were extremely interesting and informative, and it was fun to learn more about the numerous abilities sensors have to help solve problems. Maybe one day I’ll be a part of something similar to any one of these cases and be able to make a positive change while utilizing sensors to their potential.

Here are some of my thoughts regarding some of the different case studies:

Dina Cappiello’s story regarding the toxins being released into Houston’s air was fascinating. She utilized chemically reactant badges to deliver results as to how dangerous the chemicals from factories in the area were, and their potential to be harmful to residents living nearby. This was a type of non-electronic sensing. It was great to see the community coming together to become involved in the project, too. Many residents agreed to having the badges hung outside of their homes, which greatly contributed to the research and evidence that was eventually found and shared with the public. This type of sensor journalism can be used all over the world in relation to toxic chemicals being released by factories and large corporations. It could also be utilized in China, where certain areas are infested with smog and severe air pollution. The sensors could be used to determine how dangerous the smog actually is, for example, in comparison to China’s standards or what is safe for citizens and tourists to breathe in regularly.

Balloon mapping the BP oil spill along with spectrometry and trying to find the source of the spill was another interesting story. Balloon mapping could work with other natural disasters, too. It may be more difficult with forest or wildfires, but it could be possible depending on how high the flames are burning. It could also be used when earthquakes, hurricanes, or tornadoes strike to document aftermath damage.

The story regarding police officers in Florida was the most eye-opening to me. My brother wants to become a state trooper one day, and his safety is something I worry about, even before he joins the force. This specific study related to cops who were speeding on and off the job, putting both themselves and others in harm’s way. This data collection in particular seemed the most complicated, especially when Kestin and Maines were pushing to prove that their data was accurate. It was a challenging process, but a rewarding one once the data was simplified and proven to be accurate.

Just as we talked about in class, I learned a bit more about the feared cicadas in one of the case studies. Soil temperature proved to be a strong indicator of when the cicadas would arrive. The news team developed and built a sensor that anyone could do in multiple steps, and the community followed. Over 1,700 temperature readings from 800 locations allowed the data team to more intensely analyze the conditions surrounding cicadas’ arrivals.

The ShotSpotter system employed in Washington D.C. is something I wasn’t familiar with before reading the case study, but it is extremely impactful and brilliant. Essentially, microphones sit on top of buildings and rooftops, and when they hear something that sounds like gunfire, they send the data to the D.C. Metropolitan Police Department’s centralized control system. Reporters at The Washington Post looked to analyze the data to look for patterns over the years and highlight specific neighborhoods with more frequent gun use. Police departments and the reporters involved found it difficult to discern the difference between celebratory gunfire and actual gunfire, as well as fireworks during certain holidays, but informative data was published nonetheless.

Looking through SparkFun, there are hundreds of types of sensors. All of them have different abilities, but I found one that is similar in nature to the one in the case study regarding the return of cicadas. Noted here, the soil moisture sensor simply measures the moisture within soil and other similar materials. This type of sensor could be used for many different things, but my thought for a journalistic story revolves around crops, agriculture, and farming. In certain parts of the country and even throughout the world, droughts or other weather conditions exist that can cause major problems in the food and agriculture industries. This sensor could be used to determine the extent within the soil to which it can withstand and supply crops successfully without those crops dying. That way, farmers can estimate timing or situations when the soil will become too dried out for food production and find other means before planting things and wasting crops. The sensor could also be used for journalists to record different soil areas around the world and compare soil conditions with similar food production. So, if someplace in the world had the best soil for certain vegetables, the sensor would depict that soil’s moisture, and other areas could try to emulate that, either artificially or organically to lower the risk of famine or crop issues that could result at some point. Journalists could also work with farmers to measure different soil moistures for the same crop to see which measurement produces the best crop. That way, the farmers know how to best prepare their crops for the best quality and outcome possible.

Journalism alone is extremely powerful, but when you combine it with the use of sensors and the unbelievable talents of technology, people can create incredible stories that can change the trajectories of lives, science, and so much more. We are witnessing an exciting time in which technology is transforming the way we learn, live, study, and prosper, and I am excited for the future and how we as people can make a difference in this world.

pH Sensor Journalism

In the Tow Center for Digital Journalism’s report “Sensors and Journalism,” one of the most interesting parts of the case studies was how involved the public was in helping the journalists use the sensors to get data from the environment.

Although some members of the areas were concerned about what facts the data may tell, like in the Houston Chronicles “In Harms Way” study when it came to value of their properties decreasing due to poor air quality, it seemed like many people were very willing to help the journalists do research to gain a better understanding of the environment around them.

The Public Lab’s case study “Homebrew Sensing” was interesting as well because it was completely public-driven and it shows the power of activism which led to good data and good journalism.

The testing for environmental data that these case studies went for intrigued me, so when I went to Sparkfun, that is the category that I selected to find sensors that could be used for a journalistic story I thought of. I saw that Sparkfun has a full pH Sensor Kit, and I think this could be good for a story about the pH levels of tap water.

The pH level for pure water is 7.0, and the normal range for both groundwater and surface water systems is 6.5 to 8.5, according to APEC Water. The Sparkfun kit could be used to test areas that are known to have polluted water or areas that were recently affected by a large storm that could have polluted the surrounding water that the systems draw from.

Also, after doing some research on the pH levels of water, there are simple test kits that are cheap to make or order. This could also be a way to crowdsource for data and get the public involved in asking town residents to collect samples of their tap water over a week or a month. They could send the samples into a lab with their address so that the data can be put together or mapped out to show the PH level of the town’s area or even a few counties.

Assignment 3: Marita chatbot

I have to say that it was really interesting, fun and cool working on this assignment. Creating a chatbot could be so useful for different business, including media enterprises. In a personal way, I created this chatbot like an interactive resume, where people can get to know me a little bit, just like in a kind of job interview. We don’t know, but maybe in the future resumes could be like this and not a piece of paper. Who knows?

For the purpose of this chatbot, I sent a basic edition to my friends so they could interact with the bot and then I could do a better correction. However, my friends were kind of trolling my bot and navigating more in the personal bottoms, when in fact I put more effort into the professional one.

I put some links, and I tried to put the ITTT for twitter updates but it made an error on that part. I would love to insert that because it would be helpful for the purpose of the bot.

This is the chatbot “Cuban journalist”, but remember to speak Spanish!

 

Trivia Chat Bot

https://www.messenger.com/t/417543438689245

The purpose of this Chat Bot is to play a trivia game with any users who want to play. It was difficult coming up with a concept. I started off with a Joke Bot, a Riddle Bot, then eventually I decided to do a Trivia Bot.

The hardest part was trying to understand how to structure the questions and answers so that the line of conversation was in order. Eventually I figured it out but it definitely took some time. I’m glad to say I now I at least have a basic understanding of how to make a chat bot.