Stimuli Measurment and Mapping

In order to maintain consistency throughout the experiment the readings of stimuli and tracking of the tortoise was generally done between 7 and 10pm. The reasoning is that throughout the day many of the stimuli which i am testing for will fluctuate (the heat drops at night and ambient light is quite different), so since the testing will take place over many, many days a need for consistency of environment is very important. On that note, the tortoise-cam videos were actually all taken on saturday mornings because that is when the lighting in the apartment is brightest, and best for use with the tiny camera.

Apartment

A core concept of this mapping project was simply to see how the tortoise reacted just to objects and places. A top-down view of the apartment would also be handy in orienting viewers in terms of where the tortoise is in relation to other stuff in the apartment. After I measured each of the rooms, i constructed a floor plan in illustrator from which to situate my further measurements.

Then, to catalog and fill the contents of these frames, I created a gigantic panorama-like image of my apartment as seen from the top. This required taking about 500 photographs of the floor while standing on a step ladder.

The images were then roughly pieced together using photoshop's auto-aligning and auto-blending features, but I still had to do a bit of fine-tuning.

The resulting image was around 2 gigs and had a super high resolution which i had to scale back to make a version for the web.

Heat

Recording

I began the more technical mapping process by measuring a basic stimulus of life, heat. Heat seems to be a quite basic motivator, in general things tend to die if the temperature goes too far one way or the other, and since she is a cold-blooded creature, after all, I figured that heat must play a major part of her life.

Measuring the average heat of the floor was the easiest stimulus for which to test. I simply used a thermometer (technically an alarm clock with a built in thermometer) with units to 1/10 of a degree. I would first place the thermometer in a specific location on the floor of the apartment for 10 minutes (long enough for the effects of the previously measured spot to have worn off of the thermometer). After recording the value onto a spreadsheet, i then moved the thermometer to test the next spot, until a grid of values tied to locations was obtained for each room in the apartment. The resolution of the grid (the distance between single measurements) was 3 square feet.

Visualizing the Data

So that people would be able to quickly take in all this information which i had just recorded, and make judgments concerning the movement of the tortoise, i decided to visually represent the data as graded color values mapped to their location in the apartment.

First i normalized my values so that they generally ranged from 0 at the minimum temperature (67 degrees F) to 100 at the maximum floor temperature (74 degrees F). Then, after I had already mapped the layout and panoramic floor view of the apartment in Photoshop and Illustrator, I created a new gradient mesh on top of this floorplan. Next i set the Color Picker menu in Illustrator to HSB mode (Hue, Saturation, Brightness) and set the hue to 0, and brightness to 100 (for appearing hot and red). The values from the grid were then mapped to their corresponding location on the gradient mesh with a variation in the saturation of the color relating to its normalized temperature value. Thus the colder areas would appear white while warmer zones would have higher saturation values and come off as redder and hotter. Finally, since temperature gradients are typically non-discrete, i applied a Gaussian Blur to the gradient mesh to smooth the values from one test location to the next.

Sound

Whether the tortoise was even capable of hearing was a question that often came up about the pet. She doesn't seem to be too effected by speaking to her or loud noises, but she does seem to get more active when music (especially guitar music) is being played. In my research for this project i discovered that while tortoise's do not have true ears they are capable of sensing a a range of frequencies condensed to the lower to mid-range of hearing (approximately 70-300 Hz). I also later realized that this is about the range of a normally tuned guitar, which is the reasoning behind a guitar's use in later experiments. Since she is also such a creature of the ground, i figured that any low frequencies would effect her quite greatly. The mapping episode of "This American Life" is responsible for partial inspiration in how to analyze ambient sound.

Recording

To analyze the aural palette of my apartment's floor, I took a microphone attached to a camera, and placed it on the floor underneath a large, white bowl.

I figured that the bowls wide, circular mouth would simulate the effect of the tortoise's shell in how it amplifies the vibrations of the actual floor itself. I would take a 10 second audio sample, and then move the setup to the next testing location in the same grid-like pattern as with the temperature measurements.

Visualizing the Data

Before i could represent the sound data, i had to analyze it in Adobe Audition.

Using the analysis tools available in the program I was able to retreive the average frequency and RMS power for the 10 second sample from each location.Once again, i then created a new gradient mesh in Illustrator and transposed measured values from each location to color values on the mesh. This time there were two variables that needed to be represented simultaneously, frequency and power, so in HSB mode i set the hue value to the normalized frequency, and let the power correspond to the saturation. A problem that arises in dealing with sound, however, is that sounds are typically measured on a logarhithmic scale as opposed to a linear one, so i couldn't just normalize these values like the heats by just interpolating the values against a new max and min, first i would have to linearize them. Therefore to go from the logarithmic units of decibels to the linear measurement of power in Watts i had to invert the formula for decibels:

to

and then normalize the values.After the mesh was replete with values it was given the same Gaussian blur treatment to smooth out the values of the overall gradient.

Light

Recording

Unlike the process used in measuring, analyzing, and displaying the other stimuli, i was able to make use of my measuring equipment to skip a few steps. If you recall, while i was measuring the audio for the sound map i had a microphone being placed under a white bowl. To record the audio the microphone was hooked up to a camera. While the audio from the mic was being taken in, i locked the aperature settings of the camera and aimed this at the white bowl. Since all the recorded values are eventually being transposed to either Hue, Saturation, or Brightness values of the color on the gradient mesh, i could just pull an averaged color from a digital image of the white bowl and translate this directly to the mesh.

Visualizing the data

I loaded screen grabs from each clip into Adobe Illustrator, set the eyedropper/color sampling tool to its largest value, and copied the colors directly from the image of the white bowl to the gradient mesh. Then i desaturated the entire mesh so that in the final grayscale image, ambient light is simply a feature of the resulting brightness.

Smell

Volatile Organic Compounds (VOCs) are carbon based susbtances which degrade rapidly enough to cause bits of them to vaporize and float freely in the air. In other words these are substances that are generally smelly. Since pollutants tend to decay and vaporize at a much higher rate than other matierials, people typically refer to VOCs in the context of hazardous chemicals and air pollution, but VOCs can also serve as a rough indication of the relative smelliness of an area. Since most foods give off some odor and to different extents, the reading on a VOC detector near food tends to be relatively larger than barren zones, just not quite to the extent as an industrial chemical spill would have.

When Vanya cruises the apartment she will often stop to sniff a certain object, so I wanted to test the theory that perhaps certain smells would be drawing her towards places.

Recording and Data Visualiztion

The procedure for collecting and visualizing the data for smell was identical to that of the temperature measurements except that a VOC detector in a "digital canary" device was used for the testing and the data was mapped to saturation values with overall hue set to 115 degrees (the gross smelly green color).

Electro-magnetic flux

This may seem to be one of the most supernatural of the experimental stimuli and is based soley in the fact that the tortoise really seems to like wires.

Through the history of our pet ownership, this tortoise has always seemed to want to snuggle up with a good tangle of wires, or to stomp mightily around a surge protector. One time after escaping our outdoor garden, and she was feared lost after a couple of days missing, we found her near the tangle of wires under the transformer of the apartment building next door.

Recording and Data Visualiztion

The procedure for collecting and visualizing the data for smell was identical to that of the temperature measurements except that an EMF detector was used for the testing and the data was mapped to saturation values with overall hue set to 180 degrees (the electric blue).

Also a majority of the values fell within a single power of 10 but a couple of important outliers registered much higher (for instance the zone near my computer read 60 times more flux than anywhere else in my apartment). To remedy this, I assigned a multiplicative property to the hue values of the mesh to solve this problem. Therefore, whereas most regions scored on the hue value of 180 degrees (blue) the area near my computer was tweaked to a hue of 240 degrees (Magneto purple).