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Energy-efficient sampling schedules for body area networks
- in Proc. IEEE Sensors
"... Abstract — We present a novel sampling method to overcome the tradeoff between sensing fidelity and energy-efficiency in the context of localized sensor arrays used by Body Area Networks (BANs). Prior research has tackled this tradeoff as a coverage problem, wherein a subset of sensors must cover th ..."
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Cited by 4 (3 self)
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Abstract — We present a novel sampling method to overcome the tradeoff between sensing fidelity and energy-efficiency in the context of localized sensor arrays used by Body Area Networks (BANs). Prior research has tackled this tradeoff as a coverage problem, wherein a subset of sensors must cover the sensor field. Instead, we formulate it as a power-constrained sampling problem, limiting the number of samples taken per epoch to produce schedules with enhanced coverage and energy savings. This formulation capitalizes on the periodic nature and the strong spatio-temporal interactions that are innate to BAN sensor samples. Our algorithm produces schedules with over 170 % in energy savings with increased sensor coverage that yields up to a 41 % improvement in diagnostic estimates. I.
Dielectric elastomer generators for foot plantar pressure based energy scavenging
- IEEE Sensors
, 2012
"... Abstract — Parasitic energy scavenging from human-generated vibrations with piezoelectric materials has long been studied in contrast to electromagnetic or conventional electrostatic transducers. Dielectric Elastomers (DEs) are now gaining notice as low-cost electrostatic transducers with high energ ..."
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Cited by 3 (3 self)
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Abstract — Parasitic energy scavenging from human-generated vibrations with piezoelectric materials has long been studied in contrast to electromagnetic or conventional electrostatic transducers. Dielectric Elastomers (DEs) are now gaining notice as low-cost electrostatic transducers with high energy densities. However, their transduction mechanism is more intricate. DE Generators (DEGs) are functionally variable capacitors, which require fine-grained control of their charging cycles in order to maximize the energy transduced. Based on a detailed DEG model that incorporates an effective method to time the charge cycles, we contrast the energy scavenged from shoe strikes by DEGs that are virtually embedded into the shoe sole, to similar piezoelectric generators. This comparison for a plantar pressure dataset of a walking subject demonstrates a multiple order-ofmagnitude improvement in harvested energy. I.
Spatiotemporal assignment of energy harvesters on a self-sustaining medical shoe
- in Proc. IEEE Sensors
"... Abstract—We present a new method for spatiotemporal assignment and scheduling of energy harvesters on a medical shoe tasked with measuring gait diagnostics. While prior work exists on the application of dielectric elastomers (DEs) for energy scavenging onshoes,currentliteraturedoes notaddresstheissu ..."
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Abstract—We present a new method for spatiotemporal assignment and scheduling of energy harvesters on a medical shoe tasked with measuring gait diagnostics. While prior work exists on the application of dielectric elastomers (DEs) for energy scavenging onshoes,currentliteraturedoes notaddresstheissues of placement and timing of these harvesters, nor does it address integration into existing sensing systems. We solve these issues and present a self-sustaining medical shoe that harvests energy from human ambulation while simultaneously measuring gait characteristics most relevant to medical diagnosis. I.
Fault-Tolerant and Low-Power Sampling Schedules for Localized BASNs
"... Abstract—Recent advances in the scope of wearable devices and networks make body area sensor networks (BASNs) an extremely attractive tool to the fields of mobile and tele-health, owing to the range of medical applications they can serve and the diagnostic richness of patient data they can offer. Ho ..."
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Abstract—Recent advances in the scope of wearable devices and networks make body area sensor networks (BASNs) an extremely attractive tool to the fields of mobile and tele-health, owing to the range of medical applications they can serve and the diagnostic richness of patient data they can offer. However, for BASNs to achieve true ubiquity, they must be scalable in their support of automated patient data collection, making usability and reliability key considerations. Its designers must wrestle with the tradeoff be-tween usability, hindered by device intrusiveness into the behav-iors it measures, and lifetime, enhanced by large power supplies and expensive, sturdy components. Furthermore, the validity and reliability of the collected data are paramount. In this paper, we consider these issues in the context of localizedmulti-sensory wear-able networks and present a method to generate low-power sam-pling schedules that are resilient to sensor faults while achieving high diagnostic fidelity. We jointly formulate this as a power-con-strained sampling problem wherein the number of sensors sam-pled per epoch are limited, and, a fault tolerant scheduling problem wherein the sampling scheme offers enough redundancy to endure up to a predefined number of sensor faults while maintaining diag-nostic accuracy. This formulation is based on, 1) the localized scope of BASNs that engenders strong spatio-temporal interactions in the samples, and, 2) the periodic nature of human behaviorsmeasured. We present our algorithm in the context of gait diagnostics derived from a foot plantar pressure measurement platform and illustrate its performance based on real datasets collected by it. Index Terms—Body area sensor networks, energy-efficient sam-pling, fault-tolerant sampling, power-constrained sampling. I.
Dynamic Coverage Problems in Sensor Networks
"... One of the fundamental issues in sensor networks is related to analyzing the coverage, or how well a network of sensors monitors the physical space for an intrusion. The coverage is a measure of the quality of service (QoS) of the sensor network and has been the subject of various studies. The conce ..."
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One of the fundamental issues in sensor networks is related to analyzing the coverage, or how well a network of sensors monitors the physical space for an intrusion. The coverage is a measure of the quality of service (QoS) of the sensor network and has been the subject of various studies. The concept of coverage was introduced by Gage in 1992, who studied it in relation to multi-robot systems. He defined three classes of coverage problems: blanket coverage (also known as area coverage), where the goal is to achieve a static arrangement of sensing elements that maximizes the detection rate of targets appearing in the region, sweep coverage, where the goal is to move a number of sensors across the region as to maximize the probability of detecting a target, and barrier coverage, where the objective is to protect the region from unauthorized penetration. While blanket coverage is relatively well researched, the other two types of coverage have been less studied and offer much greater technical challenges. In this survey we concentrate on the two dynamic types of coverage problems, barrier and sweep coverage. We review recent results, proof techniques, analyses, and open problems and challenges. We focus on methods that allow the performance of the algorithms, i.e.
Improving Energy Efficiency in Sensing Subsystems via Near-Threshold Computing and Device Aging
"... Abstract — Near-threshold computing (NTC) has been shown to achieve maximal energy gains while maintaining performance metrics more favorable than subthreshold operation of circuits. Sensor subsystems are perfect candidates for NTC since low energy is often a crucial sensor system design desideratum ..."
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Abstract — Near-threshold computing (NTC) has been shown to achieve maximal energy gains while maintaining performance metrics more favorable than subthreshold operation of circuits. Sensor subsystems are perfect candidates for NTC since low energy is often a crucial sensor system design desideratum and speed is rarely required. However, process variation affects threshold voltages (Vth), thus forcing higher-than and lowerthan desired supply voltage (Vdd) and ground voltage (Vgnd), respectively, and results in higher switching energy. We propose to use device aging to slow those gates on the lower tail of the Vth distribution in order to increase Vgnd and reduce overall energy consumption. We present a methodology for sensor subsystem aging and observe a reduction in energy consumption by 50% over traditional settings when applying NTC and a further 15 % reduction by incorporating our sensor subsystem aging algorithms. Furthermore, we apply our developed approach for device aging at the slice-level granularity to minimize energy expenditure in FPGA systems. Through application of our techniques to simulations of FPGA designs we achieve a factor of up to 6 × over traditional operation. I.
General Terms
"... Traditional optimization methods for large multisensory networks often use sensor array reduction and sampling techniques that attempt to reduce energy while retaining full predictability of the raw sensed data. For systems such as medical sensor networks, raw data prediction is unnecessary; rather, ..."
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Traditional optimization methods for large multisensory networks often use sensor array reduction and sampling techniques that attempt to reduce energy while retaining full predictability of the raw sensed data. For systems such as medical sensor networks, raw data prediction is unnecessary; rather, only relevant semantics derived from the raw data are essential. We present a new method for sensor fusion, array reduction, and subsampling that reduces both energy and cost through semantics-driven system configuration. Using our method, we reduce the energy requirements of a medical shoe by a factor of 17.9 over the original system configuration while maintaining semantic relevance.
