Zero-power sensors with near-zero-power wakeup switches for reliable sensor platforms

Pinrod, Visarute; Pancoast, Leanna; Davaji, Benyamin; Lee, Sunwoo; Ying, Robin; Molnar, Alyosha; Lal, Amit

doi:10.1109/memsys.2017.7863640

Cited by 29 publications

(11 citation statements)

References 4 publications

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“…The power density can be calculated by Ohm’s law, which is 57 nW/cm 2 . The values are comparable to other piezoelectric nanogenerators made of lead zirconate titanate (PZT), zinc oxide (ZnO), and polyvinylidene difluoride (PVDF)-based piezoelectric materials [ 31 , 32 , 33 , 34 , 35 , 36 , 37 ], and this power density can be used for powering various types of low energy consumption sensors such as temperature sensors, electrochemical sensors, biosignals sensors, and other mechanical sensors [ 38 , 39 , 40 , 41 , 42 ]. Under 100% strain stretching, the voltage and current output slightly increased to around 0.38 V and 0.23 μA/cm 2 at the same conditions of 60 N 5 Hz, respectively ( Figures S4 and S5 in the Supplementary Materials ).…”

Section: Resultsmentioning

confidence: 53%

All 3D Printed Stretchable Piezoelectric Nanogenerator for Self-Powered Sensor Application

Zhou

Parida

Halevi

et al. 2020

Sensors

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With the rapid development of wearable electronic systems, the need for stretchable nanogenerators becomes increasingly important for autonomous applications such as the Internet-of-Things. Piezoelectric nanogenerators are of interest for their ability to harvest mechanical energy from the environment with its inherent polarization arising from crystal structures or molecular arrangements of the piezoelectric materials. In this work, 3D printing is used to fabricate a stretchable piezoelectric nanogenerator which can serve as a self-powered sensor based on synthesized oxide–polymer composites.

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Section: Resultsmentioning

confidence: 53%

All 3D Printed Stretchable Piezoelectric Nanogenerator for Self-Powered Sensor Application

Zhou

Parida

Halevi

et al. 2020

Sensors

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“…A very good approach is the one presented by Pinrod et al [49], where a combination of zero-power piezoelectric movement sensors and quasi zero-power NEMS (Nano Electro Mechanical Systems) switches are used to create a trigger-bit device that can wake up a more powerful sensor node (as a TelosB, as they illustrate). Their approach is intended to measure acceleration, magnetic field and orientation by detecting patterns using lead zirconate titanate (PZT) piezoelectric sensors.…”

Section: Zero-power Sensorsmentioning

confidence: 99%

“…In this regard, even though actuation is a key issue in the Internet of Things paradigm, in many cases it is restricted to switching on and off other systems with more capabilities in terms of actuation and processing power, or energy budget. In this context, the system is powered off and a trigger event can produce, for example, a digital action when a specific event connected to a physical parameter occurs, as in [49]. Therefore, if actuation is required, special care has to be taken to ensure that the energy budget available is enough to fulfill the requirements of the application in the edge.…”

Section: F Actuation In the Extreme Edgementioning

confidence: 99%

The Extreme Edge at the Bottom of the Internet of Things: A Review

et al. 2019

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resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This general definition shows the power that cloud computing makes available to the Internet of Things. The basic idea is to collect information, usually big amounts of data, in the point of interest (this so-called the edge, where information is generated) and upload it to be properly processed in the cloud, where ideally permanent and enough processing resources are available. This model may work perfectly with some approaches where the energy resource is not a limitation or the time required for any decision does not impose a very fast reaction. However, the cloud computing paradigm applied directly to IoT presents a set of drawbacks regarding latency, bandwidth and storage [10] because of the huge amount of data that have to be uploaded and processed. Due to these limitations, more layers have been proposed during the last years, getting closer to the source of data.

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“…To operate such systems we require energy harvesting techniques, to get what has been called zero or almost zero-power sensors. Some good examples of devices in this layer are [ 11 , 12 ]. Such devices are crucial for a future realistic implementation of the IoT paradigm and will only be able to operate by interworking with edge devices described previously.…”

Section: Related Workmentioning

confidence: 99%

Edge and Fog Computing Platform for Data Fusion of Complex Heterogeneous Sensors

Mujica

Rodriguez-Zurrunero

Wilby

et al. 2018

Sensors

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The explosion of the Internet of Things has dramatically increased the data load on networks that cannot indefinitely increment their capacity to support these new services. Edge computing is a viable approach to fuse and process data on sensor platforms so that information can be created locally. However, the integration of complex heterogeneous sensors producing a great amount of diverse data opens new challenges to be faced. Rather than generating usable data straight away, complex sensors demand prior calculations to supply meaningful information. In addition, the integration of complex sensors in real applications requires a coordinated development from hardware and software teams that need a common framework to reduce development times. In this work, we present an edge and fog computing platform capable of providing seamless integration of complex sensors, with the implementation of an efficient data fusion strategy. It uses a symbiotic hardware/software design approach based on a novel messaging system running on a modular hardware platform. We have applied this platform to integrate Bluetooth vehicle identifiers and radar counters in a specific mobility use case, which exhibits an effective end-to-end integration using the proposed solution.

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Zero-power sensors with near-zero-power wakeup switches for reliable sensor platforms

Cited by 29 publications

References 4 publications

All 3D Printed Stretchable Piezoelectric Nanogenerator for Self-Powered Sensor Application

All 3D Printed Stretchable Piezoelectric Nanogenerator for Self-Powered Sensor Application

The Extreme Edge at the Bottom of the Internet of Things: A Review

Edge and Fog Computing Platform for Data Fusion of Complex Heterogeneous Sensors

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