Did ant-based morse code today.

Ended up being a far more interesting project than I had thought it would be. At first, merely considered it a rote exercise in one of the most basic digitally augmented interactions I could place in the field. Servo with blocking door + Arduino.

But when actually doing it, performing these actions for hours with the ants, I flooded myself with new questions and concepts. Did not count on this.

1) This project features a time-dependent blockade. This is quite unlike anything these ants would experience in nature. Some sort of living creature, like an animal or plant, crossing or lying in their path could block the ants for a short or extended amount of time. This middle ground, the semi-permanence of blocking on-and-off with a regular frequency, seems unnantural.

2) What should be used as a signal? Presence or absence of ants?

3)What temporal limitations are there? Better data would come from longer blockades, but the more permanent the block, the more likely the ants will be to start a new route altogether. Short pulses give lossier data due to differences between ant walking speeds. Different limitations are also caused by different types of ants! Different limitations can also occur due to time of day, the mood of the ants, or the density of particular castes of ants that happen to be forming the current trail.

4) Factors affecting signal. -Traffic jams destroy data—> releasing too many ants before a critical junction (such as when the ant path turns to climb over a root) stop the clear sharing of information across a path. Cleanest signals come from smooth, already formed paths. The basis of this type of sinalling is that the ants move continuously with an average speed and density. Now that I think of it, these factors should be true of any signalling media, from semaphor to fiber optics. They all must have irregularities which do have some sort of impact on our communications, but so much effort has gone to quash these effects that we view certain systems (like fiber optics) as perfect models. Doing this experiment exacerbates communication problems not found much more in our high-speed data transfer systems. These ants bring the signalling quirks to the foreground at macroscales.

This can be thought to model the larger, metamessages in our new society. Not the direct, instant messaging we have mastered, but the social filtering and wide-dissemenation that we are still working on streamlining.