Demo: Unsupervised Fill-level Estimation for Smart Trash Removal Systems.

EWSN(2017)

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摘要
In this demo, we show an unsupervised, non-intrusive fill level estimation system, called Smartbin, which can be easily installed on the outside surface of waste bins to measure their occupancy levels. Smartbin uses a cheap mini-motor that exploits the physical nature of vibration resonance by learning forced vibration characteristics of the bin at different fill-levels over a small number of garbage collection cycles. This learning process occurs in a completely automated fashion ultimately enabling accurate fill level estimation that can serve as a component of smart (e.g., demand-based) trash removal services. A preliminary evaluation on six different waste bins demonstrates ability of the system to accurately measure empty, half-full, and full bin states. This physical system will be demonstrated to illustrate unsupervised learning and fill level estimation.
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