Urban Life
Urban life is largely composed of the movement, activities and familiar patterns of people within and across our crowded urban landscapes. There is also a curiosity, perhaps even verging on a voyeuristic interest in the lives of our fellow urban neighbors. As we traverse our city we share time and space with others. As we idle awaiting a bus, or navigate to our local café, we encounter other strangers.
Often unconsciously we create fictitious stories about the lives of these people – that woman owns two cats, than man is a vegan, that child is lonely. These people and the way they dress and behave on public city streets provide us an insight into the lives of others.
We conducted an Urban Probe to understand this urban space. The probe was call Jetsam that resulted in the construction of a fully functional augmented trashcan. The augmented can exposes city dwellers to the pattern of trash interactions as told from the point of view of a single city trashcan. Two event types can be sensed: interaction events and trash in/out events (including the type of trash involved). We used a simple IR photoelectrical switch to detect a basic interaction with the trashcan such as searching. A sensitive electronic scale determines the current weight of trash entering or leaving the bin. Mounted within the trashcan, an overhead camera records the top layer of trash in the bin. A laptop computer connects the devices and projects an appropriate visualization from the trashcan’s opening onto the city street There are several methods of interaction with the augmented trashcan: active, passive, and mobile.
Tossing trash into or removing trash from the augmented trashcan is an active interaction. For example, after finishing her lunch while sitting on a nearby bench, Jill tosses her bag of trash away. The augmented trashcan detects the event as the item enters the bin. Using the camera and digital scale, information about the new trash is logged. Its weight is measured and a rough image of the trash is extracted by subtracting out the previous image of the top of the trash from the current. The isolated image of the trash, its time, and weight are all logged. After a short time, an image of the individual item is introduced into the animated, projected visualization. Any individual passing near the augmented trashcan interacts passively with it by observing its shifting visualization. Recent items appear closer to the base of the trashcan and slowly “orbit” outward over time. Each trash image also rotates on its axis based on its weight with heavy items spinning slowly and light items more quickly. The resulting visualization depicts a layering of trashcan activities and patterns, not unlike the archeological layers typically found during years of drought or catastrophic change.
