Circuit and System Designs of Ultra-Low Power Sensor Nodes With Illustration in a Miniaturized GNSS Logger for Position Tracking: Part I—Analog Circuit Techniques

Jang, Taekwang; Kim, Gyouho; Kempke, Benjamin; Henry, M.; Chiotellis, Nikolaos; Pfeiffer, Carl; Kim, Dongkwun; Kim, Yejoong; Foo, Zhiyoong; Kim, Hyeongseok; Grbic, Anthony; Sylvester, Dennis; Kim, Hun-Seok; Wentzloff, David D.; Blaauw, David

doi:10.1109/tcsi.2017.2730600

Cited by 26 publications

(7 citation statements)

References 60 publications

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“…Furthermore, ultra-low power microprocessors are advisable for the use in Ambient Intelligence domains [69], [70]. Battery-free operation can then be achieved via power harvesting [71].…”

Section: Efficient Sensing Processing and Communicationmentioning

confidence: 99%

Camouflage Learning: Feature Value Obscuring Ambient Intelligence for Constrained Devices

Nguyen

Sigg

Lietzén

et al. 2023

IEEE Trans. on Mobile Comput.

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Ambient intelligence demands collaboration schemes for distributed constrained devices which are not only highly energy efficient with respect to distributed sensing, processing and communication, but which also respect data privacy. Traditional algorithms for distributed processing suffer in Ambient intelligence domains either from limited data privacy, or from their excessive processing demands for constrained distributed devices. In this paper, we present Camouflage learning, a distributed machine learning scheme that obscures the trained model via probabilistic collaboration using physical-layer computation offloading and demonstrate the feasibility of the approach on backscatter communication prototypes and in comparison with federated learning, a popular distributed learning scheme. We show that Camouflage learning is more energy efficient than traditional schemes and that it requires less communication overhead while reducing the computation load through physical-layer computation offloading. The scheme is synchronization-agnostic and thus appropriate for sharply constrained, synchronization-incapable devices. We demonstrate model training and inference on four distinct datasets and investigate the performance of the scheme with respect to communication range, impact of challenging communication environments, power consumption, and the backscatter hardware prototype.

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“…Furthermore, ultra-low power microprocessors are advisable for the use in Ambient Intelligence domains [69], [70]. Battery-free operation can then be achieved via power harvesting [71].…”

Section: Efficient Sensing Processing and Communicationmentioning

confidence: 99%

Camouflage Learning: Feature Value Obscuring Ambient Intelligence for Constrained Devices

Nguyen

Sigg

Lietzén

et al. 2023

IEEE Trans. on Mobile Comput.

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“…Because of this, the prototype instrumentation has not energy-sustainable. In an actual instrumentation, we envision energy harvesting circuits [16] that power an ultra-low microprocessor from the energy harvested through the long RF antennas [17], [18] for batteryless operation. The interested reader is referred to the good overviews available on the topic, for instance, [19]- [22] We have investigated the system only with three subjects and only exploiting 2x6 gestures in both cases.…”

Section: Limitationsmentioning

confidence: 99%

Towards battery-less RF sensing

Kodali

Nguyen

Sigg

2021

2021 IEEE International Conference on Pervasive Computing and Communications Workshops and Other Affiliated Events (PerCom Work

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Recent work has demonstrated the use of the radio interface as a sensing modality for gestures, activities and situational perception. The field generally moves towards larger bandwidths, multiple antennas, and higher, mmWave frequency domains, which allow for the recognition of minute movements. We envision another set of applications for RF sensing: battery-less autonomous sensing devices. In this work, we investigate transceiver-less passive RF-sensors which are excited by the fluctuation of the received power over the wireless channel. In particular, we demonstrate the use of battery-less RF-sensing for applications of on-body gesture recognition integrated into smart garment, as well as the integration of such sensing capabilities into smart surfaces.

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“…A reference current source is required, for example, in resistive sensing for Internet-of-things (IOT) [1] operations, in laser driving circuits for biomedical imaging [2], and in calibration circuits for current measurement systems [3]. For the IOT, because resistive sensors are used to measure diverse physical quantities, current sources providing stable sub-nA currents [4] are required for the measurement or calibration of the sensors [3]. For laser driving, a constant direct current is required to operate a laser in a continuous wave mode for medical imaging [2].…”

Section: Introductionmentioning

confidence: 99%

Microelectronic current-sourcing device based on band-to-band tunneling current

Sul

Lee²,

Kim³

et al. 2022

Nanotechnology

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A new stable current-sourcing transistor is developed using the band-to-band tunneling phenomenon. A heterojunction between thin film WS2 and heavily hole-doped bulk silicon converts a section of the WS2 contacting the silicon into a hole-doped WS2 inside the WS2 channel, and band-to-band tunneling occurs between the electron-doped and hole-doped WS2. The output current is regulated by the tunneling barrier thickness. The thickness depends on the gate bias for device switching, but is less sensitive to the source bias, enabling stable output currents. The minimum line sensitivity is 2.6%, and the temperature coefficient is 1.4×103 ppm/°C. The device can be operated as a current sourcing device with an ultralow output current and power consumption.

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Circuit and System Designs of Ultra-Low Power Sensor Nodes With Illustration in a Miniaturized GNSS Logger for Position Tracking: Part I—Analog Circuit Techniques

Cited by 26 publications

References 60 publications

Camouflage Learning: Feature Value Obscuring Ambient Intelligence for Constrained Devices

Camouflage Learning: Feature Value Obscuring Ambient Intelligence for Constrained Devices

Towards battery-less RF sensing

Microelectronic current-sourcing device based on band-to-band tunneling current

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