SoC Issues for RF Smart Dust

Cook, B.W.; Lanzisera, Steven; Pister, Kristofer S. J.

doi:10.1109/jproc.2006.873620

Cited by 145 publications

(81 citation statements)

References 90 publications

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“…Energy harvesting can be divided into four approaches: harvesting energy from motion and vibration, harvesting energy from thermal differences, photovoltaic harvesting, and RF energy harvesting [159]. The expected power from these approaches are 4-100 µW/cm 2 , 0.03-1 mW/cm 2 , 0.01-10 mW/cm 2 , and about 0.1 µW/cm 2 , respectively, which are reasonably sufficient for a sensor node in wireless sensor network applications [160]. For converting motion or vibration, the established transduction mechanisms are based on electrostatic, piezoelectric, and electromagnetic principles.…”

Section: Environment and Energy Harvestingmentioning

confidence: 99%

Review on Micro- and Nanolithography Techniques and their Applications

2012

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Abstract. This article reviews major micro-and nanolithography techniques and their applications from commercial micro devices to emerging applications in nanoscale science and engineering. Micro-and nanolithography has been the key technology in manufacturing of integrated circuits and microchips in the semiconductor industry. Such a technology is also sparking revolutionizing advancements in nanotechnology. The lithography techniques including photolithography, electron beam lithography, focused ion beam lithography, soft lithography, nanoimprint lithography and scanning probe lithography are discussed. Furthermore, their applications are summarized into four major areas: electronics and microsystems, medical and biotech, optics and photonics, and environment and energy harvesting.

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Section: Environment and Energy Harvestingmentioning

confidence: 99%

Review on Micro- and Nanolithography Techniques and their Applications

2012

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“…One such area which has benefited from low-cost miniature radios is the ability to not only acquire information from micro-sensors but also transmit this data in real time over a wireless link. For the past few years researchers are trying to explore new circuits topology for sensor node, different network methods, different radio architecture and approaches to energy scavenging which allow autonomous operation of wireless sensor network for long time [1]. At present the WSN Generally uses MESH topology of sensor nodes which individually constraint to small coverage area due to limited internal energy of fixed small size sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

“…At present the WSN Generally uses MESH topology of sensor nodes which individually constraint to small coverage area due to limited internal energy of fixed small size sensor nodes. Fig.1 MESH topology of sensor nodes previous analysis based on the well-known path loss characteristics of isotropic radiation using (1), has shown that an optimal distance between individual nodes in a collaborative mesh system theoretically yields the lowest energy consumption per bit, when transmitting a given distance "d" [1].…”

Section: Introductionmentioning

confidence: 99%

Quality of Service Optimization in Realm of Green Monitoring using Broad Area Sensor Network (BASN)

Kumar¹

2013

IOSR-JCE

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“…Such sensor nodes communicating via a wireless link for transmitting sensory data on detected events of interest can be used to build wireless sensor networks [1]- [3].…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation for Non-convex Target Object Using Networked Binary Sensors

Saitō

Tanaka

Shioda

2011

IEICE Trans. Inf. & Syst.

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SUMMARYWe describe a parameter estimation method for a target object in an area that sensors monitor. The parameters to be estimated are the perimeter length, size, and parameter determined by the interior angles of the target object. The estimation method does not use sensor location information, only the binary information on whether each sensor detects the target object. First, the sensing area of each sensor is assumed to be linesegment-shaped, which is a model of an infrared distance measurement sensor. Second, based on the analytical results of assuming line-segmentshaped sensing areas, we developed a unified equation that works with general sensing areas and general target-object shapes to estimate the parameters of the target objects. Numerical examples using computer simulation show that our method yields accurate results.

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SoC Issues for RF Smart Dust

Cited by 145 publications

References 90 publications

Review on Micro- and Nanolithography Techniques and their Applications

Review on Micro- and Nanolithography Techniques and their Applications

Quality of Service Optimization in Realm of Green Monitoring using Broad Area Sensor Network (BASN)

Parameter Estimation for Non-convex Target Object Using Networked Binary Sensors

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