Sensor Side Research Articles

Scalable real-time energy-efficient EEG compression scheme for wireless body area sensor network

Recent technological advances in wireless body sensor networks have made it possible for the development of innovative medical applications to improve health care and the quality of life. By using miniaturized wireless electroencephalography (EEG) sensors, it is possible to perform ambulatory EEG recording and real-time healthcare applications. One master consideration in using such battery-powered wireless EEG monitoring system is energy constraint at the sensor side. The traditional EEG streaming approach imposes an excessive power consumption, as it transmits the entire EEG signals wirelessly. Therefore, innovative solutions to alleviate the total power consumption at the receiver are highly desired. This work introduces the use of the discrete wavelet transform and compressive sensing algorithms for scalable EEG data compression in wireless sensors in order to address the power and distortion constraints. Encoding and transmission power models of both systems are presented which enable analysis of power and performance costs. We then present a theoretical analysis of the obtained distortion caused by source encoding and channel errors. Based on this analysis, we develop an optimization scheme that minimizes the total distortion for different channel conditions and encoder settings. Using the developed framework, the encoder can adaptively tune the encoding parameters to match the energy constraint without performance degradation.

3D silicon pixel detectors for the ATLAS Forward Physics experiment

The ATLAS Forward Physics (AFP) project plans to install 3D silicon pixel detectors about 210 m away from the interaction point and very close to the beamline (2–3 mm). This implies the need of slim edges of about 100–200 μm width for the sensor side facing the beam to minimise the dead area. Another challenge is an expected non-uniform irradiation of the pixel sensors. It is studied if these requirements can be met using slightly-modified FE-I4 3D pixel sensors from the ATLAS Insertable B-Layer production. AFP-compatible slim edges are obtained with a simple diamond-saw cut. Electrical characterisations and beam tests are carried out and no detrimental impact on the leakage current and hit efficiency is observed. For devices without a 3D guard ring a remaining insensitive edge of less than 15 μm width is found. Moreover, 3D detectors are non-uniformly irradiated up to fluences of several 1015 neq/cm2 with either a focussed 23 GeV proton beam or a 23 MeV proton beam through holes in Al masks. The efficiency in the irradiated region is found to be similar to the one in the non-irradiated region and exceeds 97% in case of favourable chip-parameter settings. Only in a narrow transition area at the edge of the hole in the Al mask, a significantly lower efficiency is seen. A follow-up study of this effect using arrays of small pad diodes for position-resolved dosimetry via the leakage current is carried out.

PCNN-Based Image Fusion in Compressed Domain

This paper addresses a novel method of image fusion problem for different application scenarios, employing compressive sensing (CS) as the image sparse representation method and pulse-coupled neural network (PCNN) as the fusion rule. Firstly, source images are compressed through scrambled block Hadamard ensemble (SBHE) for its compression capability and computational simplicity on the sensor side. Local standard variance is input to motivate PCNN and coefficients with large firing times are selected as the fusion coefficients in compressed domain. Fusion coefficients are smoothed by sliding window in order to avoid blocking effect. Experimental results demonstrate that the proposed fusion method outperforms other fusion methods in compressed domain and is effective and adaptive in different image fusion applications.

Dust Impact Monitor (DIM) onboard Rosetta/Philae: Tests with ice particles as comet analog materials

In 2014 the European Space Agency׳s spacecraft Rosetta will encounter the short-period comet 67P/Churyumov–Gerasimenko. Rosetta carries the lander spacecraft Philae on board which will attempt to land on the comet׳s nucleus. Amongst Philae׳s instruments, the Dust Impact Monitor (DIM) using piezoelectric sensors is aimed at measuring the physical properties (size and impact speed) of the millimetric and submillimetric dust and ice particles that move near the surface of comet 67P. Given that DIM has three orthogonal sensor sides (with about 70cm2) total area), it will also be able to collect dynamical data, like an estimation of the particle flux in three dimension, that will help to derive daily and secular variations in the surface activity. We show the results of a series of calibration experiments with the goal to extend the performance tests of DIM. We tested DIM under particle impacts of densities similar to and larger than that of water ice (0.92–7.80g/cm3) and at speeds from 0.3 to 1.9m/s. Then, we performed experiments with spherical water ice particles between −40°C and −20°C. Finally, we measured the coefficient of restitution (COR) of the impacting particles. These data show that there is a loss mechanism in the impact which is caused by plastic deformation in the contact zones of both the impinging particle and the PZT sensor.

Woven Textile Moisture Sensor for Enuresis Alarm Treatment

To improve comfort conditions of the enuresis alarm system, modular humidity sensor should be replaced by textile sensor. During research woven textile moisture sensor was developed and first experiments of signal detection speed were performed. Washed and unwashed samples were tested from both sides of sensor. Measurements of electrical signals were performed with oscilloscope. It is important to know what the actual resistance of a wet sensor is in order to design a proper electrical circuit that controls the state of the sensor. Acquired values of electrical resistance will be used in further sensor circuit design for developing enuresis alarm system prototype. During the design of moisture sensor it is necessary to take into consideration position of electrodes depending on sensor’s configuration and characteristics of textile wettability and moisture management.

Energy-Efficient Data Reduction Techniques for Wireless Seizure Detection Systems

The emergence of wireless sensor networks (WSNs) has motivated a paradigm shift in patient monitoring and disease control. Epilepsy management is one of the areas that could especially benefit from the use of WSN. By using miniaturized wireless electroencephalogram (EEG) sensors, it is possible to perform ambulatory EEG recording and real-time seizure detection outside clinical settings. One major consideration in using such a wireless EEG-based system is the stringent battery energy constraint at the sensor side. Different solutions to reduce the power consumption at this side are therefore highly desired. The conventional approach incurs a high power consumption, as it transmits the entire EEG signals wirelessly to an external data server (where seizure detection is carried out). This paper examines the use of data reduction techniques for reducing the amount of data that has to be transmitted and, thereby, reducing the required power consumption at the sensor side. Two data reduction approaches are examined: compressive sensing-based EEG compression and low-complexity feature extraction. Their performance is evaluated in terms of seizure detection effectiveness and power consumption. Experimental results show that by performing low-complexity feature extraction at the sensor side and transmitting only the features that are pertinent to seizure detection to the server, a considerable overall saving in power is achieved. The battery life of the system is increased by 14 times, while the same seizure detection rate as the conventional approach (95%) is maintained.

Region-Based Image-Fusion Framework for Compressive Imaging

A novel region-based image-fusion framework for compressive imaging (CI) and its implementation scheme are proposed. Unlike previous works on conventional image fusion, we consider both compression capability on sensor side and intelligent understanding of the image contents in the image fusion. Firstly, the compressed sensing theory and normalized cut theory are introduced. Then region-based image-fusion framework for compressive imaging is proposed and its corresponding fusion scheme is constructed. Experiment results demonstrate that the proposed scheme delivers superior performance over traditional compressive image-fusion schemes in terms of both object metrics and visual quality.

Development and Application of a Fast Solid-state Potentiometric CO2-sensor in Thick-film Technology

Abstract A solid-state potentiometric CO 2 sensor of the type CO 2 , O 2 , Au, Li 2 CO 3 -BaCO 3 | Nasicon | Na 2 Ti 6 O 13 -TiO 2 , Au, O 2 , CO 2 was fully manufactured in planar thick-film technology. On the rear side of the sensor substrate an integrated heater is applied. Thus, it is possible to operate the sensor as a stand-alone device. On the one hand, based on the special meander structure of the heater, a homogeneous temperature distribution on the sensor side can be obtained. And on the other hand, it is possible to operate the sensor with the ideal working temperature of 525 °C. At this temperature, the sensor signal follows the theoretical considerations and responds to the Nernst equation. That way, it is possible to use the sensor in different applications, for example to detect the CO 2 concentration of human breathing air or to monitor the air quality in closed rooms.

Random Set Methods: Estimation of Multiple Extended Objects

Random set-based methods have provided a rigorous Bayesian framework and have been used extensively in the last decade for point object estimation. In this article, we emphasize that the same methodology offers an equally powerful approach to estimation of so-called extended objects, i.e., objects that result in multiple detections on the sensor side. Building upon the analogy between Bayesian state estimation of a single object and random finite set (RFS) estimation for multiple objects, we give a tutorial on random set methods with an emphasis on multiple-extended-object estimation. The capabilities are illustrated on a simple yet insightful real-life example with laser range data containing several occlusions.

A proposed FPGA architecture for mean shift based object tracking with bandwidth constrained sensors

In this paper, we propose a CAMShift inspired object tracker for VGA resolution images implemented in an FPGA with a view to using low-cost commercially available CMOS sensors. We discuss architectural issues that arise in trying to meet the dual constraints of serialised input from a camera, and the requirement for iterative computation in the mean shift inner loop. We argue that a system oriented toward vector processing allows us to both meet our timing requirements on the sensor side and perform multiple steps of gradient ascent on the algorithm side, thus mitigating the negative effect of low input bandwidth and allowing iterative algorithms to operate within the frame acquisition time. We show how this can be implemented as a stream process with relatively low memory overhead in an Altera Cyclone IV EP4CE115F29C7FPGA found on the DE2-115 development board paired with a Terasic D5M digital camera.

The detection and thermal characterization of the inner structure of the ‘Musmeci’ bridge deck by infrared thermography monitoring

Since late 2014, the project Cloud2SM aims to develop a robust information system able to assess the long term monitoring of civil engineering structures as well as interfacing various sensors and data. Cloud2SM address three main goals, the management of distributed data and sensors network, the asynchronous processing of the data through network and the local management of the sensors themselves [1]. Integrated to this project Cloud2IR is an autonomous sensor system dedicated to the long term monitoring of infrastructures. Past experimentations have shown the need as well as usefulness of such system [2]. Before Cloud2IR an initially laboratory oriented system was used, which implied heavy operating system to be used [3]. Based on such system Cloud2IR has benefited of the experimental knowledge acquired to redefine a lighter architecture based on generics standards, more appropriated to autonomous operations on field and which can be later included in a wide distributed architecture such as Cloud2SM. The sensor system can be divided in two parts. The sensor side, this part is mainly composed by the various sensors drivers themselves as the infrared camera, the weather station or the pyranometers and their different fixed configurations. In our case, as infrared camera are slightly different than other kind of sensors, the system implement in addition an RTSP server which can be used to set up the FOV as well as other measurement parameter considerations.

RENDEZVOUS: towards fast event detecting in wireless sensor and actor networks

Fast event detection is important in wireless sensor and actor networks (WSANs) since actors can perform appropriate actions which sensor nodes are not capable to do. While WSANs inherits the typical constrains of WSNs such as energy and computation limitations of sensor nodes. In this paper, we propose a fast event detecting algorithm named RENDEZVOUS to accelerate the actor's event detecting process while keep the energy consumption of sensor nodes as minimum. When design RENDEZVOUS, we first study the mobility control of a actor to help the actor move around close to a event by using Reinforcement Learning techniques with collected sensory data. We then design a scheme to search nearby actors from the event side inspired by a searching behavior of desert ants. By both perform search actions from sensor side and actor side, the proposed algorithm can achieve fast event detecting with neglect-able additional energy cost on sensors side. Extensive simulation results demonstrate the efficiency of RENDEZVOUS.

Schedule and control co-design for networked control systems with bandwidth constraints

A new solution of networked control systems with bandwidth constraints is proposed in this paper. First, at the smart sensor side, a new stochastic communication logic scheduling strategy is designed based on a Poisson Process with time-dependent intensity. Under this strategy, the system only needs a finite-time state update. Hence the quantity of transmission of message is reduced. With the proof that the stochastic communication logic is essentially a Markov chain, the NCS is modeled as a jump system and the necessary and sufficient condition of stability for the state feedback system is presented as well. With the proposed stochastic communication logic, based on the update time, the controller is given in terms of a LMI. The simulation result shows that the scheduling strategy can decrease the network traffic, while the controller can guarantee certain good system performance.

Optimal controller location in wireless networked control systems

SUMMARYThe control performance of wireless networked control systems (WNCS) has been shown to heavily depend on the packet delivery quality of both the sensor‐to‐controller and controller‐to‐actuator communications. Such quality relies on the relative distance between the wireless transmitter and receiver, which naturally raises the challenging problem of controller placement in WNCS for optimal control performance. In this paper, we investigate the optimal controller location (OCL) problem in WNCS based on linear‐quadratic‐Gaussian control strategy. For the one‐hop network case where the controller can only be placed at either the sensor side or the actuator side, we derive a simple yet effective criterion to determine the OCL. For the more general multi‐hop case where the controller can be located at either one of the sensors, relays, or actuators, we obtain the necessary and sufficient condition under which the closed‐loop system is guaranteed to be stable. On the basis of these results, we further transform the OCL problem into an optimization problem that can be solved efficiently. Numerical results are provided to verify our analysis. Copyright © 2013 John Wiley & Sons, Ltd.

Energy efficient and reliable data delivery in urban sensing applications: A performance analysis

Urban sensing is an emerging application field for Wireless Sensor Networks (WSNs), where a number of static sensors is sparsely deployed in an urban area to collect environmental information. Data sensed by each sensor are, then, opportunistically transmitted to Mobile Nodes (MNs) that happen to be in contact. In the considered scenario, communications between MNs and sensors require paradigms with a minimal synchronization between devices, extremely fast and energy efficient, especially at the sensor side. To deal with the above issues, in [1] we proposed a hybrid protocol for data delivery from sensors to MNs, named Hybrid Adaptive Interleaved Data Protocol (HI). By combining Erasure Coding (EC) with an Automatic Repeat reQuest (ARQ) scheme, the proposed protocol maximizes the reliability of communications while minimizing the energy consumed by sensors. In this paper, we present an in-depth analysis of the HI performance. We provide an analytical evaluation by defining a flexible model to derive the probability of data delivery and exploiting it to investigate the performance over a wide range of parameters. Moreover, we perform an experimental study to evaluate the HI effectiveness on real sensor platforms. Specifically, we analyze the impact of resource constraints imposed by sensors on data delivery and provide a careful characterization of its actual consumption of resources.

Modifying the risk-benefit ratio using drug delivery systems

Urban sensing is an emerging application field for Wireless Sensor Networks (WSNs), where a number of static sensors is sparsely deployed in an urban area to collect environmental information. Data sensed by each sensor are, then, opportunistically transmitted to Mobile Nodes (MNs) that happen to be in contact. In the considered scenario, communications between MNs and sensors require paradigms with a minimal synchronization between devices, extremely fast and energy efficient, especially at the sensor side. To deal with the above issues, in [1] we proposed a hybrid protocol for data delivery from sensors to MNs, named Hybrid Adaptive Interleaved Data Protocol (HI). By combining Erasure Coding (EC) with an Automatic Repeat reQuest (ARQ) scheme, the proposed protocol maximizes the reliability of communications while minimizing the energy consumed by sensors. In this paper, we present an in-depth analysis of the HI performance. We provide an analytical evaluation by defining a flexible model to derive the probability of data delivery and exploiting it to investigate the performance over a wide range of parameters. Moreover, we perform an experimental study to evaluate the HI effectiveness on real sensor platforms. Specifically, we analyze the impact of resource constraints imposed by sensors on data delivery and provide a careful characterization of its actual consumption of resources.

Multi-Energy X-Ray Imaging System Using Single Photon Counting

High-performance computing capability enabled the development of a multi-energy X-ray imaging system which includes a data-acquisition, pre-processing and transmission module, followed by image reconstruction module. The data acquisition, pre-processing and transmission module are located at the pixel sensor side, and the image reconstruction is completed by using a GPGPU on a host PC. Thus, it requires a high-speed communication channel between the sensor side and the host PC. In this paper, we introduce our prototype multi-energy X-ray system focusing on the data acquisition, pre-processing, and transmission module. The experimental results demonstrate the feasibility of our proposal to the single photon counting X-ray system.

Dust Impact Monitor (DIM) onboard Rosetta/Philae: Comparison of experimental results and the theory behind the experiment

The Dust Impact Monitor (DIM) experiment on board the Rosetta spacecraft's lander, Philae, is a cube with three sides covered with piezo-electric (PZT) sensors (total sensitive area: ≈70cm2), aimed at measuring the physical properties of millimetric and sub-millimetric dust particles that move near the surface of comet 67P/Churyumov—Gerasimenko. In this work we study the performance of the DIM Flight Spare (FS) unit based on impact experiments and compare the measurements with the sensor's expected theoretical behavior as derived from Hertz' theory of elastic impact. We present the results of impact experiments performed with spherical particles of different densities and elastic properties. We performed two types of experiments: (a) we analyze the performance of the different sensor sides under identical impacts, and (b) we investigate the performance of DIM under impacts of different materials and different impact speeds. We discuss the possible influence of the microstructure of the PZT sensor on the signal strength and its variation with position of the impacting particles. Our results show that the signal strength and the contact times measured with the DIM PZT sensors can be well approximated by Hertz’ contact mechanics.

A Hybrid Authenticated Group Key Agreement Protocol in Wireless Sensor Networks

Wireless sensor networks are a modern and advanced technology whose applications are fast developing in recent years. Despite being a fascinating topic with various visions of a more intelligent world, there still exist security issues to be resolved in order to make WSNs fully adoptable. Due to the resource constraints of sensor nodes, it is infeasible to use traditional key establishment techniques that find use in fixed communication systems. In this paper, the design of a new hybrid Authenticated Group Key Agreement (AGKA) protocol is described for WSNs. The AGKA protocol reduces the high cost public-key operations at the sensor side and replaces them with efficient symmetric-key based operations. The proposed AGKA protocol is not only efficient but also meets strong security requirements. In order to demonstrate the protocol is verifiably secure and trustworthy, a formal verification of the AGKA protocol is carried out. Furthermore, several experiments are conducted on MICAz and TelosB platforms in order to evaluate the performance of the proposed protocol. The evaluation results show that the AGKA protocol is well suited for use with resource-constrained sensor nodes.

A numerical study on the influence of insulating layer of the hot disk sensor on the thermal conductivity measuring accuracy

A numerical study on the influence of the insulation layer of the hot disk sensor on the thermal conductivity measuring accuracy has been conducted. It is found that the influences of the thermal contact resistance and the insulating layer could be excluded in the transient plane source method. Both the kapton5501 and the mica5082 sensor could measure stainless steel and ceramic with a deviation less than 3% while the deviation increases to 54.2% of silica aerogel because of the large heat loss proportion through the mica5082 sensor side. The simulation proved that the heat loss through sensor side and accuracy could be improved by increasing the radius of the sensor.