Smart Dust: Communicating with a Cubic-Millimeter Computer

By B. Warneke, M. Last, Brian Liebowitz, Kristofer S. J. Pister. Computer, 2001

798 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/368eb95e2edf53983070d98478dd250a5cd43fc9

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In Computer Networks and Communications

Citations in the corpus

Schottky-quantum dot photovoltaics for efficient infrared power conversion (2008, background): “Other infrared power conversion applications include thermophotovoltaic (TPV) cells, which convert thermal emissions into electrical power for co-generation of heat and electricity [10]; and wireless power distribution [11], which would benefit from using eyesafe (wavelengths > 1.”
On-chip antennas in silicon ICs and their application (2005, background): “Such nodes could help to accelerate the realization of the Smart Dust vision [ 14 ].”
TinyOS: An Operating System for Sensor Networks (2005, background): “Single-chip systems are now emerging that integrate a low-power CPU and memory, radio or optical communication [75], and MEMS-based on-chip sensors.”
Internet of things: Vision, applications and research challenges (2012, background): “Indeed, current technologies are far from the level of integration foreseen in the SmartDust vision [65].”
Low energy adaptive clustering hierarchy with deterministic cluster-head selection (2002, background): “Distributed wireless microsensor networks are an important component of the world of Ubiquitous Computing [2],[3].”
The nesC language: a holistic approach to networked embedded systems (2003, background): “…brewer@cs.berkeley.edu culler@cs.berkeley.edu EECS Department Intel Research, Berkeley University of California, Berkeley 2150 Shattuck Ave, Suite 1300 Berkeley, CA 94720 Berkeley, CA 94704 ABSTRACT We present nesC, a programming language for networked embedded systems that…”
Passive UHF RFID antennas for sensing applications: Principles, methods, and classifcations (2013, background): “The ultimate goal is to design “smart dust motes” [5], i.”
Online outlier detection in sensor data using non-parametric models (2006, background): “Advances in processor technologies and wireless communications have enabled the deployment of small, low cost and power efficient sensor nodes in both civil and military settings [43, 24].”
Trajectory based forwarding and its applications (2003, background): “Examples of such vision include smartdust [1], dataspaces [2, 3], sensitive skin [4], or disposable networks where it is possible that many of the nodes of the network can be sprayed, dropped, mixed in the material or embedded in the infrastructure.”
Perspectives in Ornithology: Application of tracking and data-logging technology in research and conservation of seabirds (2009, neutral): “A decade ago, “smart-dust” technology was envisaged: millimeter-sized motes capable of sensing, storing, and transmitting information on the environment (Warneke et al. 2001).”
Wireless sensor networks: a survey (2002, background): “…integrated patient monitoring; diagnostics; drug administration in hospitals; monitoring the movements and internal processes of insects or other small animals; telemonitoring of human physiological data; and tracking and monitoring doctors and patients inside a hospital [8] [42] [60] [71] [88].”
An energy efficient hierarchical clustering algorithm for wireless sensor networks (2003, background): “The Smart Dust Project at University of California, Berkeley [14, 15, 16] and WINS Project at UCLA [1, 17], are two of the research projects attempting to build such low-cost and extremely small (approximately 1 cubic millimeter) sensors.”