Look, Learn, Ask, Try: Geran, Kyle & Terrence

This one was a little weird for us because our application spans across several paradigms so it was hard to scope exactly who we were going to study and ask questions about.  However Brint Carlson, a personal friend of mine, is currently a tank engineer in ROTC here at ASU and since he was an easy point of contact I went ahead and brought the idea up to him.

Look: I observed him doing some training out in the desert, this time in particular it was medical.  I was granted permission since it was a school project however I was not allowed to take any photos or video because it’s the military so they weren’t super stoked about that.  However the exercise was to discover fellow soldiers in need, asses their issue and respond accordingly.

Ask: I asked them what typical things happen ‘in the field’ and how does one go about helping them?  They responded that most often there are a team of medics and they are usually the only ones qualified to handle said situations.  Not many people are equipped with the tools or expertise to asses a soldier in need.

Learn: I learned that one of the biggest problems is communication and that it is hard to find the people in need or when they do locate them, they realize they didn’t have the necessary equipment for the task at hand and thus they need to go back to camp and grab the gear which can sometimes take too long, resulting in a fatality. We couldn’t exactly ‘try’ this activity of course but we can speculate that if we have some kind of equipment to alert local medics about the condition of a soldier it could save a lot of time locating them and bringing the correct equipment for the job.

Try: As far as ‘trying’ goes, I have started to implement a machine learning aspect to the eeg helmet that can try an categorize different conditions of the brain.  eMotiv actually has a large database that you can subscribe to that will show you common data structures for different things like seizures, massive sudden pain trauma, elevated endorphins etc.  So at some point I would like to train some data sets and see if I can detect matches to different scenarios and situations.  Of course I don’t want to fake a seizure or something so the scenarios will have to be more mild like being happy or sad or frightened.

 

Status Update: Hazardous and Safety Conditions Wearable. Geran, Terrence & Kyle.

So far we have implemented the more hands-on portion of our project by testing out both the Google glass and the Epoc+ helmet from eMotiv.  It is taking a bit to get the two to jive as far as the data but we are able to harness visual data and eeg data simultaneously which was basically the end goal for the proof of concept aspect of the project.

 

Below is a simultaneous reading of my eeg signals while wearing the Google glass to display data and record video.  This displays all the necessary eeg waves while recording the environment.

 

In the coming days if we have the chance I would like to pipe the eeg data into a max patch if it is possible through the serial port and do a small machine learning aspect with wekinator.  However this is not a priority as our speculative design is much more important for the bio-design challenge.

The real next few steps are to design one or more speculative designs that are futuristic in nature and can span across different markets.  The end product wouldn’t be and eeg helmet and a pair of glasses but more of and instertable or a wearable device tailored for the application at hand.  For example we could make small instertables for elderly folk in a nursing home, special military applications for a group on a secret mission or even given out to the population during a natural disaster time.  Each speculative design would have it’s own capabilities and implementation.  The elderly home may be equipped with a heart rate monitor and gps in case the patient has a history of wandering off which happens quite often when elderly people suffer from dementia.  The military application could track pain through eeg signals and alert neighboring forces if someone is in trouble.  The populous wearable could be equipped with whatever is necessary for the disaster at hand be it a wildfire, hurricane or tsunami.

From here on out we will do the following:

Geran- Continue developing Google glass / Epoc helmet to get some consistent results to show a more usable application in the future.  Also help with speculative designs.

Kyle- Develop ideas for different speculative designs with Terrence.  Also organize and prepare our presentation and exactly how we plan to tackle the correct audience for the product.  Narrow down our research and end goals.

Terrence- Develop ideas for different speculative designs and how many different applications we may want to involve ourselves in.  Make some 3D models of potential designs and how/why they would work.

 

 

Look, Ask, Learn, Try- Justin Maroney, Ben Nandin, Daisy Nolz, Shomit Barua

For our project, we observed an urban public space on campus to try and understand better how our green building technology would effect pedestrians within a city.

Look: For the look portion we used the “fly on the wall” approach. The area we observed was surrounded mostly by buildings with some landscaping. One interesting observation we made was the number of bugs just from having some simple landscaping in the area, as well as people’s aversions to areas with more visible bugs. Mitigation of pests in environments constructed mostly from plants is definitely something we need to consider when thinking about our project.

Ask: We decided to elicit feedback on our general idea from normal people in the area we observed by simply telling them our project idea and asking for any opinions or thoughts they had on it. Most people gave general, brief feedback. Most of the answers were along the lines of “that sounds really interesting”. However, one person took a bit more interest. He was mostly interested in the structural integrity of the technology. Having this conversation made use realize our lack of answer for this question. This is something for us to take into consideration. however, our understanding of this facet of our project is definitely considerably limited my our lack of expertise in that area.

Try: Based on some of our observations from our Look activity, we wanted to personally experience being in the different microbiomes within the area we were observing. We tried sitting in areas near more obvious bug populations and in areas seemingly void of bugs, as well as areas of more and less dense plant population. Something interesting we experienced was a noticeable drop in air temperature in the areas more with denser vegetation.

Learn: based on our observations from both our look and try methods, we learned more about the impact our technology could have on outdoor public spaces. It could be beneficial by providing shade and cooler environments, however it could also invite unwanted pests to the public areas as well, causing people to be less inclined to conjugate in those areas.

These were the three main sports we observed.

Project Status Update–Ben, Shomit, Justin and Daisy.  

Our project is using the excess waste materials from brewing and distilling alcohol to build buildings and imagine futures where this is actualized. We want to use the grains mixed with other organic substances like coffee grounds to form bricks then grow root systems in them to strengthen them. The roots will act like a binding agent.

We do not have code to implement at this time, but we do have the above pictures of sketches and designs for our prototype we are currently implementing. We are creating mock ups of different brick structures and how they interact with the plants. We also have our shared google slide presentation that we have previously shared in class and our google document.

Until the Showcase deadline Daisy and Justin will be fabricating these example models and trying to create a real living plant model. Shomit will be polishing the presentation format, and Ben will be focusing on code.

Jinlong, Ruipeng, Shanshan, Zhenping-Look, ask, learn, try

Our group project is about to avoid back pain while in long distant ridding and try to apply a new technology that the suit can absorb the sweat to power up the product. In order to know if this concept is feasible, we decided to interview our classmate who is call Heartin and he is a fan of cycling. We met him at his home.

 

Look: 

We found that he has three bikes at his home and he told us that he will trying to do a long distant cycling after this semester.

 

Ask:

Our team: what do you think of this concept?

Heartin: The idea is great! Back pain is a common ailment in long distant cycling. I have back pain, which is very uncomfortable during cycling. Also, the suit is very cool, absorbing sweat to power up the device.

Our team: Do you have question about this idea?

Heartin: Here is a one thing I care about. Since the device will be included in the suit, so it has to be flexible and very small. So, how long this device can be used? Usually, if I plan to do long distant cycling, it will take five to seven hours. I am wondering if this product can be used at least five to seven hours.

Our team: Do you have any suggestion to this product?

Heartin: Normally, there are two reasons to cause back pain. The first is the wrong ridding posture. The second is that cyclist have to take a rest if they ride too long. Even though this device can help you to keep a appropriate ridding posture, you have to consider to add a timer to remind cyclist they need to have a rest.

 

Try:

 In order to have a deeper understanding of the project. We asked him to show us the wrong ridding posture in long distant cycling. What’s more, we also consider to place our product in back of the suit. Thus, we asked him to try which part and what kind of shape will be the best place for the product.

Learn:

Here is an opportunity that we found during the interview. We found that sometimes he will lean to left or right while cycling. He said that a lot of people have this problem in long distant cycling. It is also not good for your back. Thus, we can apply three bend sensors in the device, one of straight, two for left and right. If people lean to left or right side, the bend sensors will detect the cyclist in the wrong posture, then the device will vibrate to remind them.

 

Project Update – Jennifer, Michael, Damon, Will

After looking over a lot of the feedback that we received on our mycelium island project our group came to the conclusion, with the help of others from the class, that the idea overall is not feasible/believable. And so, we have chosen to focus more on the idea of mycelium eating plastic in a smaller scale project. We are looking to make either a new form of recyclable trash can made of mycelium, or some sort of instillation that mimics the general idea. For the deliverable, we are thinking of making a silicon mold from a simple waste basket, and from there grow mycelium from it. Since we don’t have an actual strain of mycelium that eats plastic, we were thinking of making a stop motion video showing our mycelium trash can eating plastic or something along those lines. If chosen for the challenge, we would try to design a 3D printed version of the mold and grow the mycelium from that.