NOTE: Lumia Learning does not capture any camera footage or data other than to track when a person enters the space in front of it and the length to which they stay. Each person that enters Lumia Learning's view is anonymized and no recognition beyond body presence / skeletal tracking is utilized. 

Report 3 - Monday, July 26th

Right now, I use a variety of remote tools to check on Lumia Learning, making sure it's functioning without having to physically be in proximity of the piece. At its best this allows me to seamlessly make sure that everything is working properly, and to watch the live data roll in... at its worst it can feel a bit like observing a rover on an alien planet with all the quirks and small errors and glitches that entails. Still, the experiment and piece continue and fighting errors simply becomes routine. All that aside, after being pushed and pulled back to status quo over the past week, Lumia Learning is starting to undergo some changes... 

In the previous two data reports, I noted that Lumia Learning was seeing viewers approaching so frequently that there was little room for any one color to stand out. As soon as one did so, it would be cancelled out by the equal pull over the next loop iterations in the opposite direction. This meant that in terms of color, Lumia Learning was stagnant - simply doing a full spectrum color sweep repeatedly. However, this weekend, Lumia Learning observed enough of a color preference that it is starting to tip in one direction. Initially, I admit that I was skeptical of the changes, as, when looking at the graphed data it does not appear that any preference is being indicated...


Grouping those colors together into broader spectrum values, however, reveals the impetus for shifting.


(For added clarity - prior to the weekend observations, those groups were all at 20% equally.) We can see that blue colors are observed 4% more often than orange colors as the piece cycles through the spectrum, causing Lumia Learning to lean in this direction. This preference has previously been so slight that it was easily counter-balanced. Now, however, as the piece errs on the side of that color, it's safe to predict that the feedback loop will cause blues to be preferred as Lumia Learning shows them at a higher rate than the others. Or not! We'll see. For now, blue colors will appear more often and for longer as the piece tips that direction. 

Lumia Learning is still observing a preference for faster speeds in the moving shapes and continues to incrementally ramp them up. The 'drag' on this data is caused by the fact that slower speeds are still somewhat popular - faster speeds simply more so. Still, the data bears out that faster speeds are preferred and the speedometer slowly ticks up for speed of motion within the piece. 

Hue Ramp
While color and speed have been easily observed (albeit slow to change), hue ramp testing has been harder to quantify. For reference, the moving shapes within Lumia Learning operate on both a color spectrum sweep and a linear ramp-and-fall for hue. This, in an effort to prevent the colors from being the same on background and foreground, and thus, becoming just a static color. Beginning today, Lumia Learning will be testing to see if there is preference in how this hue ramps and falls, moving between a linear ramp like this...


And a parabolic ramp like this... 


...while testing alternative swaps (Ramp Down/Up, Parabolic Up) for preference between. Once the piece has a clear tipping point toward one, it will begin offsetting this against the background color to try to reach an ideal. Time will tell where Lumia Learning takes that data from here. For now, it sits in the planet Del Amo Fashion Center, observing the fauna and attempting to learn.

Report 2 - Wednesday, July 21st


In the first bits of data coming from Lumia Learning, we saw that color choice was inconclusive - with so many people viewing the piece over the course of its twenty minute loops, that there was very little opportunity for the piece *not* to be tracking a person. This was especially true of opening day - a Saturday and the opening of the Ultra! exhibition - in which the numbers of viewers trended so much higher than on a weekday. So much so that those weekend viewers are bearing heavy weight on the data going forward. For example, Lumia Learning has observed that light green was conclusively and by far the most observed color on Tuesday. What the data obscures however, is how few individuals observed the piece that day as compared to the weekend. Which is how we get from a Tuesday color preference chart like this...


To an overall color preference chart like this...


(Forgive the styling differences. The first is the raw data that Lumia Learning spits out, the second is my cleaned up ongoing dashboard.) Here, we see that the great middling effect I spoke of in the text surrounding the piece is coming to fruition. A broad enough observation of participants results in a lack of consensus and a middling of nearly everything being preferred equally - despite clear preferences being shown on a smaller scale. While green, light green, mustard yellow, tangerine, deep orange, and indigo hold slight edges above their neighboring colors, they aren't enough to push or pull the color in any one direction as of yet, as they tend to counter each other out. I suspect that, much like the crowds at your local movie theater, weekend viewers will be the element that provides for more decisive sway. That, or, the piece will continue to shift ever so slightly and come to rest in the middle of the spectrum where it began...

The speed of motion of the piece, on the other hand, continues to hold out trends that faster motion is preferred. The piece is already changing direction, but as with color, is tempered slightly in that weekday viewership simply isn't producing large swings in the data. This means that a faster preference observed Saturday and Sunday holds out by sheer number, not by the individual preferences for each day. As a result, and to try to filter some noise out of the data observed, Lumia Learning will reverse the order of the loops so that the faster speeds play in the first loop, rather than the last. This might produce an interesting result - as in, maybe people like to look at Lumia Learning at the bottom of the hour for other reasons. Or, maybe it won't! Again, weekends will likely be paramount in producing shifts, and we will wait and see. For now, Lumia Learning trends slightly faster, and will favor not only that speed moving forward, but will prioritize it in order of playthrough. 


Report 1 - July 17th - Opening Day


Inconclusive findings on color. Lumia Learning has observed that while a deep yellow orange tangerine is the most observed color, it is still very closely followed by a more mustard yellow, green, and violet.

Numbers on colors are still very even across the board, and likely more data will be required to push the piece to noticeable difference.

While color preference may be inconclusive, preferences in speed show a more drastic trend. Lumia Learning currently cycles through three speeds over the course of an hour. Speed 3 showed drastic preference during yesterday's observation, garnering viewers at a rate of nearly 2 to 1. As a result, Lumia Learning will move its shapes faster and test for a higher threshold of speed preference going forward.

Hue Ramp
The moving shapes operate currently on a linear hue ramp. This will be tested on a day against day basis. Results will arrive in the coming days about the preference of hue ramp.