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Low Power Embedded Sensing: Hardware-Software Design and Applications

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A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (31 December 2017) | Viewed by 40924

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Special Issue Editors

Dr. Michele Magno

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Guest Editor

Department of Electronic Informatic Technology and Electric Engineering (ITIT), ETH Zürich, 8092 Zürich, Switzerland
Interests: low power embedded systems; sensors systems; wireless sensor networks; energy harvesting; low power machine learning; microcontrollers; energy efficiency
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Prof. Dr. Vedran Bilas

E-Mail Website
Guest Editor

Department of Electronic Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia
Interests: electromagnetic induction sensing; sensor interfaces and signal processing; networked embedded sensors; low power electronic systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 8th EAI Conference on Sensor Systems and Software is a single-track forum for research on system development and software support for embedded sensing, broadly defined. This year, the conference will be organized in co-location with SoftCom, in Split, Croatia. Full Conference papers with an extension of at least 50% of content can be submitted to the Special Issue.

This Special Issue emphasizes the challenges, issues, and opportunities in the research, design, and engineering of sensing devices, focusing on techniques, strategies, and algorithms applied to real life applications. More in detail, the Special Issues is focused on contributions in the area of low power and energy efficient devices and systems that employ sensors to achieve smart applications. The aim of this Special Issue is to attract researchers and practitioners from academia and industry, on the following topics of interest:

·         New hardware and sensing platforms
·         Architectures for energy-neutral sensing systems
·         Power management algorithms for energy harvesting sensing systems
·         Sensor data processing, storage and management
·         Energy efficient deep learning for smart camera
·         Wake up radio and energy efficient communication
·         Wearable sensing technologies (smart textile, wearable electronics)
·         Zero-power sensing for long term monitoring
·         Experiences of real-world low-power sensing applications and deployments
·         Smart-X applications involving sensing, monitoring and control

Dr. Michele Magno
Prof. Dr. Vedran Bilas
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Low Power Sensor Devices
Energy Efficient Sensor Interfaces
Always on Mixed Signal Sensor Interfaces
Low Power Sensor Signal Processing
Energy Efficient Deep Learning
Zero Power Binary Sensors
Zero Power Transponders
Energy Harvesting
Power Management
Compressive Sensing
Energy Efficient Communication
Smart Environments
Smart Devices
Wearable Sensors
Sensing Applications

Published Papers (6 papers)

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Research

15 pages, 4764 KiB

Open AccessArticle

Flow Control in Wells Turbines for Harnessing Maximum Wave Power

by Jon Lekube, Aitor J. Garrido, Izaskun Garrido, Erlantz Otaola and Javier Maseda

Sensors 2018, 18(2), 535; https://doi.org/10.3390/s18020535 - 10 Feb 2018

Cited by 35 | Viewed by 4539

Abstract

Oceans, and particularly waves, offer a huge potential for energy harnessing all over the world. Nevertheless, the performance of current energy converters does not yet allow us to use the wave energy efficiently. However, new control techniques can improve the efficiency of energy converters. In this sense, the plant sensors play a key role within the control scheme, as necessary tools for parameter measuring and monitoring that are then used as control input variables to the feedback loop. Therefore, the aim of this work is to manage the rotational speed control loop in order to optimize the output power. With the help of outward looking sensors, a Maximum Power Point Tracking (MPPT) technique is employed to maximize the system efficiency. Then, the control decisions are based on the pressure drop measured by pressure sensors located along the turbine. A complete wave-to-wire model is developed so as to validate the performance of the proposed control method. For this purpose, a novel sensor-based flow controller is implemented based on the different measured signals. Thus, the performance of the proposed controller has been analyzed and compared with a case of uncontrolled plant. The simulations demonstrate that the flow control-based MPPT strategy is able to increase the output power, and they confirm both the viability and goodness. Full article

(This article belongs to the Special Issue Low Power Embedded Sensing: Hardware-Software Design and Applications)

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19 pages, 828 KiB

Open AccessArticle

RESTOP: Retaining External Peripheral State in Intermittently-Powered Sensor Systems

by Alberto Rodriguez Arreola, Domenico Balsamo, Geoff V. Merrett and Alex S. Weddell

Sensors 2018, 18(1), 172; https://doi.org/10.3390/s18010172 - 10 Jan 2018

Cited by 38 | Viewed by 4343

Abstract

Energy harvesting sensor systems typically incorporate energy buffers (e.g., rechargeable batteries and supercapacitors) to accommodate fluctuations in supply. However, the presence of these elements limits the miniaturization of devices. In recent years, researchers have proposed a new paradigm, transient computing, where systems operate directly from the energy harvesting source and allow computation to span across power cycles, without adding energy buffers. Various transient computing approaches have addressed the challenge of power intermittency by retaining the processor’s state using non-volatile memory. However, no generic approach has yet been proposed to retain the state of peripherals external to the processing element. This paper proposes RESTOP, flexible middleware which retains the state of multiple external peripherals that are connected to a computing element (i.e., a microcontroller) through protocols such as SPI or I

^{2}

C. RESTOP acts as an interface between the main application and the peripheral, which keeps a record, at run-time, of the transmitted data in order to restore peripheral configuration after a power interruption. RESTOP is practically implemented and validated using three digitally interfaced peripherals, successfully restoring their configuration after power interruptions, imposing a maximum time overhead of 15% when configuring a peripheral. However, this represents an overhead of only 0.82% during complete execution of our typical sensing application, which is substantially lower than existing approaches. Full article

(This article belongs to the Special Issue Low Power Embedded Sensing: Hardware-Software Design and Applications)

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3242 KiB

Open AccessArticle

A Tuned-RF Duty-Cycled Wake-Up Receiver with −90 dBm Sensitivity

by Sadok Bdiri, Faouzi Derbel and Olfa Kanoun

Sensors 2018, 18(1), 86; https://doi.org/10.3390/s18010086 - 29 Dec 2017

Cited by 21 | Viewed by 5868

Abstract

A novel wake-up receiver for wireless sensor networks is introduced. It operates with a modified medium access protocol (MAC), allowing low-energy consumption and practical latency. The ultra-low-power wake-up receiver operates with enhanced duty-cycled listening. The analysis of energy models of the duty-cycle-based communication is presented. All the WuRx blocks are studied to obey the duty-cycle operation. For a mean interval time for the data exchange cycle between a transmitter and a receiver over

1.7

s

and a 64-bit wake-up packet detection latency of 32 ms, the average power consumption of the wake-up receiver (WuRx) reaches down to 3 μ

W

. It also features scalable addressing of more than 512 bit at a data rate of 128

k

bit

s

⁻¹. At a wake-up packet error rate of

10^{- 2}

, the detection sensitivity reaches a minimum of

- 90

dBm

. The combination of the MAC protocol and the WuRx eases the adoption of different kinds of wireless sensor networks. In low traffic communication, the WuRx dramatically saves more energy than that of a network that is implementing conventional duty-cycling. In this work, a prototype was realized to evaluate the intended performance. Full article

(This article belongs to the Special Issue Low Power Embedded Sensing: Hardware-Software Design and Applications)

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3288 KiB

Open AccessArticle

Anti-Sweep Jamming Design and Implementation Using Multi-Channel Harmonic Timing Sequence Detection for Short-Range FMCW Proximity Sensors

by Zhijie Kong, Ping Li, Xiaopeng Yan and Xinhong Hao

Sensors 2017, 17(9), 2042; https://doi.org/10.3390/s17092042 - 06 Sep 2017

Cited by 16 | Viewed by 6697

Abstract

Currently, frequency-modulated continuous-wave (FMCW) proximity sensors are widely used. However, they suffer from a serious sweep jamming problem, which significantly reduces the ranging performance. To improve its anti-jamming capability, this paper analyzed the response mechanism of a proximity sensor with the existence of real target echo signals and sweep jamming, respectively. Then, a multi-channel harmonic timing sequence detection method, using the spectrum components’ distribution difference between the real echo signals and sweep jamming, is proposed. Moreover, a novel fast Fourier transform (FFT)-based implementation was employed to extract multi-channel harmonic information. Compared with the traditional band-pass filter (BPF) implementation, this novel realization scheme only computes FFT once, in each transmission cycle, which significantly reduced hardware resource consumption and improved the real-time performance of the proximity sensors. The proposed method was implemented and proved to be feasible through the numerical simulations and prototype experiments. The results showed that the proximity sensor utilizing the proposed method had better anti-sweep jamming capability and ranging performance. Full article

(This article belongs to the Special Issue Low Power Embedded Sensing: Hardware-Software Design and Applications)

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6860 KiB

Open AccessArticle

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

by Jinmeng Rao, Yanjun Qiao, Fu Ren, Junxing Wang and Qingyun Du

Sensors 2017, 17(9), 1951; https://doi.org/10.3390/s17091951 - 24 Aug 2017

Cited by 48 | Viewed by 11684

Abstract

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction. Full article

(This article belongs to the Special Issue Low Power Embedded Sensing: Hardware-Software Design and Applications)

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7777 KiB

Open AccessArticle

Novel Concrete Temperature Monitoring Method Based on an Embedded Passive RFID Sensor Tag

by Yongsheng Liu, Fangming Deng, Yigang He, Bing Li, Zhen Liang and Shuangxi Zhou

Sensors 2017, 17(7), 1463; https://doi.org/10.3390/s17071463 - 22 Jun 2017

Cited by 25 | Viewed by 6773

Abstract

This paper firstly introduces the importance of temperature control in concrete measurement, then a passive radio frequency identification (RFID) sensor tag embedded for concrete temperature monitoring is presented. In order to reduce the influences of concrete electromagnetic parameters during the drying process, a T-type antenna is proposed to measure the concrete temperature at the required depth. The proposed RFID sensor tag is based on the EPC generation-2 ultra-high frequency (UHF) communication protocol and operates in passive mode. The temperature sensor can convert the sensor signals to corresponding digital signals without an external reference clock due to the adoption of phase-locked loop (PLL)-based architecture. Laboratory experimentation and on-site testing demonstrate that our sensor tag embedded in concrete can provide reliable communication performance in passive mode. The maximum communicating distance between reader and tag is 7 m at the operating frequency of 915 MHz and the tested results show high consistency with the results tested by a thermocouple. Full article

(This article belongs to the Special Issue Low Power Embedded Sensing: Hardware-Software Design and Applications)

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