Better late than never is what they say right? Well after a few speed bumps, the ultimate surveillance tool is complete!

Spybrero from Tommy Doyle on Vimeo.

The Spybrero uses a raspberry pi in conjunction with a raspberry pi camera module to create a spy cam. The raspberry pi (via the GPIO pins) is attached to conductive thread that runs down the sides of the sombrero into the shirt of the user. The thread then continues down the sleeve to the button at the end of the sleeve. When the button is pressed, the program on the raspberry pi takes a photo and saves it to the SD card.

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I was thinking about how I wanted to rework my project when I had to watch a video on Philip Zimbardo’s theory of Past, Present, and Future-orientation for my Dexign for Future class. At the same time, I was researching art projects about memories and came across this Memory and Loss installation:

www.terirueb.net/old_www/trace/paper.html

Merging the two ideas together, I came up with the idea for a rethink of the memory box. I have carried my memory box to each of the 17 apartments I’ve had as an adult but I never look into it unless I’m moving. And then only for few minutes. The rememory box would allow you to interact with your memories on a regular basis.

password: rememory

Circles in Motion from Dan Russo on Vimeo.

In biology class we learn about the heart, how it pumps blood throughout the body, and how oxygen is inhaled through the lungs. When you lift you inhale and exhale to maximize movements, but why do you do this? How does one know they are training their body in a healthy way or when their muscles are fatigued (rather than based on feeling)?

Heart Monitor – To know what ones heart rate is we measure the pulse. Using an LED the change in color on the finger tells when blood is moving.

Electromyography (EMG) is used to determine muscle fatigue

“Fatigue is a phenomena that accompanies repeated muscular exertion. The ability of the muscle to produce force is reduced as fatigue occurs. Local muscle fatigue is manifested in electromyography (EMG) signals by a shift in the EMG power spectrum from high to low frequencies.” (www.sbir.gov/sbirsearch/detail/259138)

How can this information be simplified to a user and be understood in a different way outside of the realm of medicine? Should visualizations of the body be included?

Current Market

Mio Link

Heart Monitor with Bluetooth connectivity, acknowledges current training zone by color on the wristband. Images below is off of the Mio Website . It indicates the 5 heart rate zones that are tracked by the heart rate monitor.

www.mioglobal.com/Default.aspx

My Issues: The wristband shows a simple out put of color, but you have to remember what that means and how it is important to incorporate that into your workout, a feed back of why and how long would be helpful to explain what the training is doing. You know you body is at its max due to red, but how fatigued are your muscles compared to heart rate?

Components:

I am currently using the products below to extract data and understand it to the simplest of variables so create a component that outputs the information in a simplified, non-medical manner.

EMG Spikershield from Backyard Brains

backyardbrains.com/products/emgSpikershield

PulseSensor by PulseSensor

pulsesensor.myshopify.com/

password: teletickle

iVolume is a device that allows you to listen to your favorite radio station on Pandora, where the volume of the music is controlled based on how loud or quiet the surrounding environment is. As someone who loves listening to music on Pandora, I thought this would be an interesting way to use the input from the microphone, and a productive way to get my hands dirty with the Raspberry Pi.

The video above has illustrated the basic working of the device. The electret microphone amplifier senses the crowd noise, where the data is interpreted and sent to the Raspberry Pi through Serial communication. Pianobar, an open-source, console-based client for Pandora, comes with many features including playing, managing, and rating stations. For this project, I used the input data to manipulate the volume of the music. In the video, I plugged in a set of speakers to the Raspberry Pi to illustrate how the device works. However, a more ideal setting would be to use headphones instead because the microphone will take in the loud sound from the speakers, which will eventually make the volume go up and never come down.

Even though there are quite a number of tutorials for Pianobar + Raspberry Pi, I learned a lot working on this project. This includes figuring out how to manually install the libraries onto the Raspberry Pi, working in terminal, sending data from an Arduino to a RPi, and coding in Python. Looking forward, I plan to create a more durable and portable prototype, and possibly mix in other types of inputs to manage the different stations.

Here is the video of how the Spy Object works.

Github Repository is here

When the program is run, camera takes three consecutive photographs. Every image is scanned to determine dominant color of every pixel. Pixels are converted into dominant color (either red , green or blue). Now, entire image is scanned to determine dominant color of the entire image. This color is printed out. If all three images are of a predefined color sequence, an audio file is played. If the sequence does not match, program returns nothing.

Lessons Learned–
1.The original idea was to to do face detection using RPi. We couldn’t find much precedence on that, also processing via RPi makes it very slow. The only method of doing it is creating a database of predetermined face (say 9 different expressions and angles) and train the Pi to detect the face using this database. This method is not scalable since if more faces are to be detected, larger database has to be built, which can not be handled in Pi.
2. We reduced the size of the image (160×120 pixels) to decrease the time it takes to process the image. Processing time is very high for images larger than that.
3. Color detection is not very accurate. We don’t know if it is the lights, reflection or the camera. Camera can detect the dominant color of a pixel(orange to pink are taken in as red and so on for blue and green) but differentiating between three closely related colors proved to be difficult. Possible solution here would be to print RGB value for a colored object and then manually determine a range of detection.

I have a new idea for my final project: a Tangible Command Line (working title)

The concept of the unix terminal is a difficult one to grasp if you haven’t grown up with it. My idea is simple: provide a tool for learning how to use the command line, by converting archaic black-on-white cryptic text to physical blocks, flags, and connections. There are a variety of tools out there that attempt to do the same thing, but nothing I could find that reaches into the physical world.

Some inspirational products:

Illucia

Illucia is a video game controller inspired by Moog and Buchla devices. It passes OSC commands via physical wire between programs.

Littlebits

Littlebits are small single-purpose electronic components that connect together with magnets to produce an easy-to-make circuit.

explainshell.com

A website that prompts the user for a complicated shell command, and returns it annotated with relevant manpage sections.

Example commands and concepts:
Pipes (|), Redirects (>/<), Flags (-), sudo, ls, cd, grep, ssh, vnc, make, python, nano, mv, cp, rm, chmod, mkdir, pwd