Tracking Real-World Phenomena with Smart Dust

So-called “Smart Dust” is envisioned to combine sensing, computing, and wireless communication capabilities in an autonomous, dust-grain-sized device. Dense networks of Smart Dust should then be able to unobtrusively monitor real-world processes with unprecedented quality and scale. In this paper, we present and evaluate a prototype implementation of a system for tracking the location of real-world phenomena (using a toy car as an example) with Smart Dust. The system includes novel techniques for node localization, time synchronization, and for message ordering specifically tailored for large networks of tiny Smart Dust devices. We also point out why more traditional approaches developed for early macro prototypes of Smart Dust (such as the Berkeley Motes) are not well suited for systems based on true Smart Dust.

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