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Smart Dust: communicating with a cubic-millimeter computer
Abstract
The Smart Dust project is probing microfabrication technology's limitations to determine whether an autonomous sensing, computing, and communication system can be packed into a cubic millimeter mote (a small particle or speck) to form the basis of integrated, massively distributed sensor networks. Although we've chosen a somewhat arbitrary size for our sensor systems, exploring microfabrication technology's limitations is our fundamental goal. Because of its discrete size, substantial functionality, connectivity, and anticipated low cost, Smart Dust will facilitate innovative methods of interacting with the environment, providing more information from more places less intrusively.
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Cited by
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Beeby, S. P., Tudor, M. J., & White, N. M. (2006) · Measurement Science and Technology · doi:10.1088/0957-0233/17/12/r01 · Cited by 3,008
Classifications, applications, and design challenges of drones: A review
Hassanalian, M., & Abdelkefi, A. (2017) · Progress in Aerospace Sciences · doi:10.1016/j.paerosci.2017.04.003 · Cited by 1,454
A Pervasive Body Sensor Network for Measuring Postoperative Recovery at Home
Aziz, O., Atallah, L., Lo, B., ElHelw, M., Wang, L., Yang, G. Z., & Darzi, A. (2007) · Surgical Innovation · doi:10.1177/1553350607302326 · Cited by 91
Metadata
- Authors
- Warneke, B., Last, M., Liebowitz, B., & Pister, K. S. J.
- Venue
- Computer
- Published
- 2001
- Volume
- 34
- Issue
- 1
- Pages
- 44-51
- ISSN
- 0018-9162 (ISSN-L)
- OpenAlex
- W3117609753
- Cited by
- 697
- References
- 0
- FWCI
- 77.45
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Smart Dust: communicating with a cubic-millimeter computer. https://app.cochat.ai/papers/10.1109/2.895117
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- Warneke, B., Last, M., Liebowitz, B., & Pister, K. S. J. (2001). Smart Dust: communicating with a cubic-millimeter computer. Computer. https://doi.org/10.1109/2.895117
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
