Max Ladabaum is a finalist from our first Neosensory developer contest. We are excited to host the following guest write-up from him about the Buzz AC field detector!
Making information more intuitive
I used to wish that I was superman. Not so that I could have super strength, or heat vision, or even the ability to fly. I wanted to be Superman so that I wouldn’t have to go to school.
In my 12-year-old eyes, the most impressive of all of Superman’s abilities was that he was able to learn an entire planet’s worth of knowledge while floating from Krypton to Earth in his space pod. With the help of a voice assistant, Baby Superman passively learned everything about his home planet, whereas I had to go to school for seven hours a day. What an outrage!
Ever since my initial frustration of not being able to learn passively, I have been obsessed with extracting patterns from the natural world and making them simple to understand. Why should I be forced to read a musical score, note by note, when I can just listen to a song instead? Similarly, why should I have to learn complicated equations about electromagnetism when I could just feel electromagnetic phenomena through my wrist instead? Imagine how much easier it would be to wire a house or fix a powerline if our knowledge of electromagnetism was intuitive, as opposed to calculated. One could go so far as to imagine a future where wiring is so easy that dads no longer take pride in getting the TV to work!
Taking a leaf out of the (song) book
When I try to think of the gold standard of data representation—a way of encoding information that feels intuitive and passive to my brain—I think of music. When I listen to music, I can easily recognize if the tempo of a song has changed or if a note is out of key. On the contrary, if I read sheet music, it is extremely challenging to recognize an out of key or off-beat note.
Let’s assume that I want to “absorb” a song into my brain. I can either read the musical score, using my sense of sight to look at musical notation on a page, or I can listen to the song, using my sense of hearing to listen to pressure waves traveling through the air. Upon initial consideration, it doesn’t seem like pressure waves in the air are any easier to “absorb” than musical notation on a page. However, it just so happens that our brains have trained since birth to be able to interpret sound pressure waves as music. This fact makes listening to the song much easier and more convenient than looking at musical notation on a page.
Unfortunately, most modern technologies related to electromagnetism require that people “read the musical score” (process inconveniently mapped information) as opposed to “listen to the music” (process conveniently mapped information). Instead of processing inconveniently mapped information, wouldn’t it be nice to have a device, similar to a mechanical player piano or a speaker, that maps information streams into forms that are easy for the human brain to process?
The Buzz AC field detector
In the case of the Buzz AC field detector, my goal from the start has been to make processing information about electromagnetic phenomena as intuitive as listening to music. The goal is straightforward, but the execution is complicated. To begin with, it is hard to identify which types of mappings are easy for the brain to “make sense” of. One possibility is that the ideal way to absorb information through the skin is through outlier selection in the time domain. In layman’s terms, changes in tempo and frequency may be the easiest and most intuitive way for the brain to process information through the skin. If this is the case, it is probably because the world is awash with oscillating phenomena—it would make sense that a brain optimized for living in a world of oscillations would be good at understanding oscillating patterns.
Based on the concept of encoding information through oscillations, I have designed the Buzz AC field detector to map electromagnetic signals into beat frequencies. Similar to how a pendulum of length L will oscillate with a natural frequency and period, motors 1, 2, and 3 are programmed such that they each measure signals at their own assigned “natural processing frequencies.” The electromagnetic field also oscillates at a frequency, usually 60Hz in the United States, corresponding to the frequency of the electrical grid. A unique beat frequency is expressed by each motor based on the difference between the natural frequency of the motor and the frequency of the EM field.
Figure: The measured frequency of the EM field is 60Hz. The natural frequency of motor 1 is set to 62Hz, the natural frequency of motor 2 is set to 60.1Hz, and the natural frequency of motor 3 is set to 57Hz. Motor 1 will pulse with a beat of 2Hz (62Hz – 60Hz), motor 2 will pulse with a beat of 0.1Hz (60.1Hz – 60Hz), and motor 3 will pulse with a beat of 3Hz (57Hz-60Hz).
Sensing electromagnetic fields
In the scenario described above, a user can sense the frequency, strength, and modes of the EM field by feeling the 2Hz, 0.1Hz, and 3Hz beats created by the differences between the natural frequencies of each motor and the EM field frequency. As the EM field frequency changes, the beat frequency of each motor changes. Based on these changes, the user can feel that the EM field frequency has changed, by how much it has changed, and in what direction it has changed.
The motor vibration also changes in accordance to the amplitude of the EM field signal. For example, if a user is a few feet away from a 60Hz signal, they should feel motors 1, 2, and 3 each pulsing at their own unique beat frequencies. As the user gets closer to the 60Hz signal, the amplitude (intensity) of each motor’s vibration will increase but the beat frequencies will not change.
Buzz AC field detector users are able to feel if one EM field signal is oscillating at a different frequency or amplitude than another, but are not able to sense the exact numerical values associated with the frequency and amplitude of the signal. This is similar to how a normal Buzz user can feel a vibration at a specific location and know its general pitch and intensity, but cannot feel the exact numerical values associated with the note’s volume and tone. In both cases, all that matters is that the motors consistently map data relative to a specific structure.
The fastest way to understand signals
Ok, this makes sense, but why did I go through all of the trouble of mapping EM field data into beat frequencies? Couldn’t I have just turned everything into Morse code and sent it through Buzz? In theory, it may be possible that after many years of “listening” to Morse code through Buzz it would become easy to understand. However, Buzz AC field detector users don’t have years to learn how to understand signals. Efficient information mappings tailored to specific sensory inputs, (in this case, electromagnetic field information mapped to beat frequencies), are a great way to speed up the learning process. The more intuitive the mapping, the faster a user can understand and make use of the electromagnetic field data. Additionally, intuitive mappings require less attention, thereby bringing the user experience closer to the initial goal of passive understanding.
Interested in building your own amazing sensory expanding applications? Dive in by checking out our developer site and developer posts on our blog. If you have any questions regarding this project or a project you’re working on, visit the Neosensory developer Slack. If you create your own project and would like to share it, email us at firstname.lastname@example.org – we’ll feature select projects on our site in the coming months!