Showing papers on "Data acquisition published in 2013"

Compressed Sensing Signal and Data Acquisition in Wireless Sensor Networks and Internet of Things

Abstract: The emerging compressed sensing (CS) theory can significantly reduce the number of sampling points that directly corresponds to the volume of data collected, which means that part of the redundant data is never acquired. It makes it possible to create standalone and net-centric applications with fewer resources required in Internet of Things (IoT). CS-based signal and information acquisition/compression paradigm combines the nonlinear reconstruction algorithm and random sampling on a sparse basis that provides a promising approach to compress signal and data in information systems. This paper investigates how CS can provide new insights into data sampling and acquisition in wireless sensor networks and IoT. First, we briefly introduce the CS theory with respect to the sampling and transmission coordination during the network lifetime through providing a compressed sampling process with low computation costs. Then, a CS-based framework is proposed for IoT, in which the end nodes measure, transmit, and store the sampled data in the framework. Then, an efficient cluster-sparse reconstruction algorithm is proposed for in-network compression aiming at more accurate data reconstruction and lower energy efficiency. Performance is evaluated with respect to network size using datasets acquired by a real-life deployment.

Method and apparatus for intelligent acquisition of position information

Abstract: Improved methods and systems for position acquisition and/or monitoring are disclosed. The position acquisition and/or monitoring can be performed with improved intelligence so that data acquisition, transmission and/or processing is reduced. As a result, the position acquisition and/or monitoring is able to be performed in a power efficient manner.

Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree

Abstract: High-level triggering is a vital component of many modern particle physics experiments. This paper describes a modification to the standard boosted decision tree (BDT) classifier, the so-called bonsai BDT, that has the following important properties: it is more efficient than traditional cut-based approaches; it is robust against detector instabilities, and it is very fast. Thus, it is fit-for-purpose for the online running conditions faced by any large-scale data acquisition system.

Fast full-color computational imaging with single-pixel detectors

Abstract: Single-pixel detectors can be used as imaging devices by making use of structured illumination These systems work by correlating a changing incident light field with signals measured on a photodiode to derive an image of an object In this work we demonstrate a system that utilizes a digital light projector to illuminate a scene with approximately 1300 different light patterns every second and correlate these with the back scattered light measured by three spectrally-filtered single-pixel photodetectors to produce a full-color high-quality image in a few seconds of data acquisition We utilize a differential light projection method to self normalize the measured signals, improving the reconstruction quality whilst making the system robust to external sources of noise This technique can readily be extended for imaging applications at non-visible wavebands

Magnetic Field Response Measurement Acquisition System

Abstract: Magnetic field response sensors designed as passive inductor-capacitor circuits produce magnetic field responses whose harmonic frequencies correspond to states of physical properties for which the sensors measure. Power to the sensing element is acquired using Faraday induction. A radio frequency antenna produces the time varying magnetic field used for powering the sensor, as well as receiving the magnetic field response of the sensor. An interrogation architecture for discerning changes in sensor's response frequency, resistance and amplitude is integral to the method thus enabling a variety of measurements. Multiple sensors can be interrogated using this method, thus eliminating the need to have a data acquisition channel dedicated to each sensor. The method does not require the sensors to be in proximity to any form of acquisition hardware. A vast array of sensors can be used as interchangeable parts in an overall sensing system.

Image acquisition and model selection for multi-view stereo

Abstract: . Dense image matching methods enable efficient 3D data acquisition. Digital cameras are available at high resolution, high geometric and radiometric quality and high image repetition rate. They can be used to acquire imagery for photogrammetric purposes in short time. Photogrammetric image processing methods deliver 3D information. For example, Structure from Motion reconstruction methods can be used to derive orientations and sparse surface information. In order to retrieve complete surfaces with high precision, dense image matching methods can be applied. However, a key challenge is the selection of images, since the image network geometry directly impacts the accuracy, as well as the completeness of the point cloud. Thus, the image stations and the image scale have to be selected according carefully to the accuracy requirements. Furthermore, most dense image matching solutions are based on multi-view stereo algorithms, where the matching is performed between selected pairs of images. Thus, stereo models have to be selected from the available dataset in respect to geometric conditions, which influence completeness, precision and processing time. Within the paper, the selection of images and the selection of optimal stereo models are discussed according to to photogrammetric surface acquisition using dense image matching. For this purpose, impacts of the acquisition geometry are evaluated for several datasets. Based on the results, a guideline for the acquisition of imagery for photogrammetric surface acquisition is presented. The simple and efficient capturing approach with "One panorama each step" ensures complete coverage and sufficiently redundant observations for a surface reconstruction with high precision and reliability.

Fundamental understanding on the use of Bluetooth scanner as a complementary transport data

Abstract: Literature is limited in its knowledge of the Bluetooth protocol based data acquisition process and in the accuracy and reliability of the analysis performed using the data. This paper extends the body of knowledge surrounding the use of data from the Bluetooth Media Access Control Scanner (BMS) as a complementary traffic data source. A multi-layer simulation model named Traffic and Communication Simulation (TCS) is developed. TCS is utilised to model the theoretical properties of the BMS data and analyse the accuracy and reliability of travel time estimation using the BMS data.

A generalized empirical interpolation method : application of reduced basis techniques to data assimilation

Abstract: This paper, written as a tribute to Enrico Magenes, a giant that has kindly and warmly supported generations of young researchers, introduces a generalization of the empirical interpolation method (EIM) and the reduced basis method (RBM) in order to allow their combination with data mining and data assimilation. The purpose is to be able to derive sound information from data and reconstruct information, possibly taking into account noise in the acquisition, that can serve as an input to models expressed by partial differential equations. The approach combines data acquisition (with noise) with domain decomposition techniques and reduced basis approximations.

Surface EMG Signal Amplification and Filtering

Abstract: Electromyographic (EMG) signals have been widely employed as a control signal in rehabilitation and a means of diagnosis in health care. Signal amplification and filtering is the first step in surface EMG signal processing and application systems. The characteristics of the amplifiers and filters determine the quality of EMG signals. Up until now, searching for better amplification and filtering circuit design that is able to accurately capture the features of surface EMG signals for the intended applications is still a challenging. With the fast development in computer sciences and technologies, EMG signals are expected to be used and integrated within small or even tiny intelligent, automatic, robotic, and mechatronics systems. This research focused on small size amplification and filtering circuit design for processing surface EMG signals from an upper limb and aimed to fix the amplifiers and filters inside a robotic hand with limited space to command and control the robot hand movement. The research made a study on the commonly used methodologies for EMG signal processing and circuitry design and proposed a circuit design for EMG signal amplification and filtering. High-pass filters including secondorder and fourth-order with the suppression to low frequency noises are studied. The analysis, verification and experiment showed that a second-order high-pass filter can adequately suppress the low frequency noises. The proposed amplification and filtering circuit design is able to effectively clean the noises and collect the useful surface EMG signals from an upper limb. The experiment also clearly revealed that power line interference needs to be carefully handled for higher signalnoise-ratio (SNR) as a notch-filter might cause the loss of useful signal components. Commercial computer software such as LabView and Matlab were used for data acquisition software development and data analysis. General Terms EMG data acquisition, Bio-signal processing, Bio-informatics

Fundamental understanding on the use of Bluetooth scanner as a complementary transport data

Abstract: Literature is limited in its knowledge of the Bluetooth protocol based data acquisition process and in the accuracy and reliability of the analysis performed using the data. This paper extends the body of knowledge surrounding the use of data from the Bluetooth Media Access Control Scanner (BMS) as a complementary traffic data source. A multi layer simulation model named Traffic and Communication Simulation (TCS) is developed. TCS is utilised to model the theoretical properties of the BMS data and analyse the accuracy and reliability of travel time estimation using the BMS data.

SmartSync: An Integrated Real-Time Structural Health Monitoring and Structural Identification System for Tall Buildings

Abstract: This study introduces a unique prototype system for structural health monitoring (SHM), SmartSync, which uses the building’s existing Internet backbone as a system of virtual instrumentation cables to permit modular and largely plug-and-play deployments. Within this framework, data streams from distributed heterogeneous sensors are pushed through network interfaces in real time and seamlessly synchronized and aggregated by a centralized server, which performs basic data acquisition, event triggering, and database management while also providing an interface for data visualization and analysis that can be securely accessed. The system enables a scalable approach to monitoring tall and complex structures that can readily interface a variety of sensors and data formats (analog and digital) and can even accommodate variable sampling rates. This study overviews the SmartSync system, its installation/operation in the world’s tallest building, Burj Khalifa, and proof-of-concept in triggering under dual e...

Compressed sensing reconstruction for whole-heart imaging with 3D radial trajectories: a graphics processing unit implementation.

Abstract: A disadvantage of three-dimensional (3D) isotropic acquisition in whole-heart coronary MRI is the prolonged data acquisition time. Isotropic 3D radial trajectories allow undersampling of k-space data in all three spatial dimensions, enabling accelerated acquisition of the volumetric data. Compressed sensing (CS) reconstruction can provide further acceleration in the acquisition by removing the incoherent artifacts due to undersampling and improving the image quality. However, the heavy computational overhead of the CS reconstruction has been a limiting factor for its application. In this article, a parallelized implementation of an iterative CS reconstruction method for 3D radial acquisitions using a commercial graphics processing unit is presented. The execution time of the graphics processing unit-implemented CS reconstruction was compared with that of the C++ implementation, and the efficacy of the undersampled 3D radial acquisition with CS reconstruction was investigated in both phantom and whole-heart coronary data sets. Subsequently, the efficacy of CS in suppressing streaking artifacts in 3D whole-heart coronary MRI with 3D radial imaging and its convergence properties were studied. The CS reconstruction provides improved image quality (in terms of vessel sharpness and suppression of noise-like artifacts) compared with the conventional 3D gridding algorithm, and the graphics processing unit implementation greatly reduces the execution time of CS reconstruction yielding 34-54 times speed-up compared with C++ implementation.

A laser scanning-based method for fast estimation of seismic-induced building deformations

Abstract: Monitoring damaged buildings in an area where an earthquake has occurred requires the use of techniques which provide rapid and safe measurements even in emergency conditions. In particular, remote sensing techniques like terrestrial laser scanning (TLS) can satisfy these requirements, since they produce very dense point clouds in little time and also allow an accurate geometric modeling of observed buildings. Nevertheless, strong constraints on TLS data acquisition geometry, such as acquisition distance and incidence angles, typically characterize an area in seismic emergency conditions. In order to correctly interpret the data, it is necessary to estimate errors affecting TLS measurements in these critical conditions. A reliable estimation can be achieved by means of experiments and numerical simulations aimed at quantifying a realistic noise level, with emphasis on reduction of artifacts due to data acquisition, registration and modeling. This paper proposes a data analysis strategy in which TLS-based morphological maps computed as point-to-primitive differences are created. The method can be easily used for accurate surveying in emergency conditions. In order to demonstrate the proposed method in very diverse situations, it was applied to rapidly detect deformation traces in the San Giacomo Roncole Campanile (Modena), the Asinelli tower (Bologna) and the Cantalovo Church (Verona), three buildings damaged by the Mw 5.9 Emilia Romagna 2012 earthquake (Italy).

TinyOS-based real-time wireless data acquisition framework for structural health monitoring and control

Abstract: SUMMARY Wireless smart sensor networks have become an attractive alternative to traditional wired sensor systems to reduce implementation costs of structural health monitoring systems. The onboard sensing, computation, and communication capabilities of smart wireless sensors have been successfully leveraged in numerous monitoring applications. However, the current data acquisition schemes, which completely acquire data remotely prior to processing, limit the applications of wireless smart sensors (e.g., for real-time visualization of the structural response). Although real-time data acquisition strategies have been explored, challenges of implementing high-throughput real-time data acquisition over larger network sizes still remain because of operating system limitations, tight timing requirements, sharing of transmission bandwidth, and unreliable wireless radio communication. This paper presents the implementation of real-time wireless data acquisition on the Imote2 platform. The challenges presented by hardware and software limitations are addressed in the application design. The framework is then expanded for high-throughput applications that necessitate larger networks sizes with higher sampling rates. Two approaches are implemented and evaluated on the basis of network size, associated sampling rate, and data delivery reliability. Ultimately, the communication and processing protocol allows for near-real-time sensing of 108 channels across 27 nodes with minimal data loss. Copyright © 2012 John Wiley & Sons, Ltd.

O(ε)-Approximation to physical world by sensor networks

Abstract: To observe the complicate physical world by a WSN, the sensors in the WSN senses and samples the data from the physical world. Currently, most of the existing work use equi-frequency sampling methods (EFS) or EFS based sampling methods for data acquisition in sensor networks. However, the accuracies of EFS and EFS based sampling methods cannot be guaranteed in practice since the physical world usually varies continuously, and these methods does not support reconstructing of the monitored physical world. To overcome the shortages of EFS and EFS based sampling methods, this paper focuses on designing physical-world-aware data acquisition algorithms to support O(ϵ)-approximation to the physical world for any ϵ ≥ 0. Two physical-world-aware data acquisition algorithms based on Hermit and Spline interpolation are proposed in the paper. Both algorithms can adjust the sensing frequency automatically based on the changing trend of the physical world and given c. The thorough analysis on the performance of the algorithms are also provided, including the accuracies, the smooth of the outputted curves, the error bounds for computing first and second derivatives, the number of the sampling times and complexities of the algorithms. It is proven that the error bounds of the algorithms are O(ϵ) and the complexities of the algorithms are O(1/ϵ1/4). Based on the new data acquisition algorithms, an algorithm for reconstructing physical world is also proposed and analyzed. The theoretical analysis and experimental results show that all the proposed algorithms have high performance in items of accuracy and energy consumption.

Design and Experimental Characterization of a Pumping Kite Power System

Abstract: The pumping kite concept provides a simple yet effective solution for wind energy conversion at potentially low cost. This chapter describes a technology demonstrator which uses an inflatable membrane wing with 20 kW nominal traction power on a single-line tether. The focus is on the innovative and scientifically challenging development aspects, especially also the supervisory control and data acquisition system designed for automatic operation. The airborne hardware includes a Kite Control Unit, which essentially is a remote-controlled cable manipulator, and the inflatable wing with its bridle system allowing for maximum de-powering during the retraction phase. On the ground, the drum/generator module is responsible for traction power conversion while constantly monitoring and adapting the force in the tether. The control software includes two alternating autopilots, one for the lying figure eight maneuvers during tether reel-out and one for the reel-in phase. As a result of monthly test-operation since January 2010, large quantities of measurement data have been harvested. The data acquisition and post-processing is presented and discussed for representative conditions. The power curve of the system and other characteristic operational parameters are determined by a statistical analysis of available data and compared to the results of a theoretical performance analysis.

Intelligent electronic device and method thereof

Abstract: An intelligent electronic device (IED) having a gain control unit adapted to selectively regulate operating ranges of output signals of a sensing circuit of the device is described. In one embodiment, the IED is a digital electric power and energy meter, which operating ranges for supply voltages and supply currents of electrical services may be adjusted to match pre-determined ranges for input signals of a data acquisition system or a data processing module of the meter.

Utility-driven data acquisition in participatory sensing

Abstract: Participatory sensing (PS) is becoming a popular data acquisition means for interesting emerging applications. However, as data queries from these applications increase, the sustainability of this platform for multiple concurrent applications is at stake. In this paper, we consider the problem of efficient data acquisition in PS when queries of different types come from different applications. We effectively deal with the issues related to resource constraints, user privacy, data reliability, and uncontrolled mobility. We formulate the problem as multi-query optimization and propose efficient heuristics for its effective solution for the various query types and mixes that enable sustainable sensing. Based on simulations with real and artificial data traces, we found that our heuristic algorithms outperform baseline approaches in a multitude of settings considered.

Fluorescence molecular tomography of an animal model using structured light rotating view acquisition.

Abstract: In recent years, an increasing effort has been devoted to the optimization of acquisition and reconstruction schemes for fluorescence molecular tomography (FMT). In particular, wide-field structured illumination and compression of the measured images have enabled significant reduction of the data set and, consequently, a decrease in both acquisition and processing times. FMT based on this concept has been recently demonstrated on a cylindrical phantom with a rotating-view scheme that significantly increases the reconstruction quality. In this work, we generalize the rotating-view scheme to arbitrary geometries and experimentally demonstrate its applicability to murine models. To the best of our knowledge this is the first time that FMT based on a rotating-view scheme with structured illumination and image compression has been applied to animals.

A Survey of Model-based Sensor Data Acquisition and Management

Abstract: In recent years, due to the proliferation of sensor networks, there has been a genuine need of researching techniques for sensor data acquisition and management. To this end, a large number of techniques have emerged that advocate model-based sensor data acquisition and management. These techniques use mathematical models for performing various, day-to-day tasks involved in managing sensor data. In this chapter, we survey the state-of-the-art techniques for model-based sensor data acquisition and management. We start by discussing the techniques for.

Optimization of acquisition setup for cross-hole GPR full-waveform inversion using checkerboard analysis

Abstract: Tomographic inversions of cross-hole ground-penetrating radar provide images of electromagnetic properties of the shallow subsurface and are used in a wide range of applications. Whereas the resolutions of ray-based methods like first-arrival traveltime and first-cycle amplitude tomography are limited to the scale of the first Fresnel zone, full-waveform inversions incorporate precise forward modelling using the full recorded signal for a solution of Maxwell’s equation, which results in sub-wavelength resolutions. In practice, the method can be time-consuming in data acquisition and expensive in computational costs. To overcome these expenses, a semi-reciprocal acquisition setup with a reduced number of transmitters and an interchange of transmitter and receiver boreholes instead of a one-sided equidistant setup in either borehole yielded promising results. Here, this optimized, semi-reciprocal acquisition setup is compared to a dense, equidistant, one-sided acquisition setup measured at the field site Krauthausen, Germany. The full-waveform inversion results are evaluated using the checkerboard test as a capable resolution analysis tool to determine resolvabilities. We introduced also a new method of time-zero correction by a cross-correlation of a zerooffset profile with corresponding horizontal traces of each multi-offset gather. The obtained experimental results from Krauthausen combined with the checkerboard analysis indicate the main threepermittivity layers that correspond with different porosities. Also fine-layered structures within these main layers were reliably imaged. We conclude that the use of the semi-reciprocal setup is optimum for acquisition speed, inversion speed and obtained permittivity inversion results. Our results indicate that conductivity results are better for denser transmitter-receiver setups.

Data acquisition method and device for motion recognition, motion recognition system and computer readable storage medium

Abstract: A data acquisition method and device for motion recognition, a motion recognition system and a computer readable storage medium are disclosed. The data acquisition device for motion recognition comprises: an initial motion recognition module adapted to perform an initial recognition with respect to motion data collected by a sensor and provide motion data describing a predefined range around a motion trigger point to a data storage module for storage; a data storage module adapted to store motion data provided from the initial motion recognition module; and a communications module adapted to forward the motion data stored in the data storage module to a motion computing device for motion recognition. The present invention makes an initial selection to the motion data to be transmitted to the motion computing device under the same sampling rate. Consequently, the present invention reduces pressures on wireless channel transmission and wireless power consumption, and provides high accuracy in motion recognition while providing motion data at the same sampling rate.

Methods of Manufacturing Data Acquisition for Production Management - A Review

Abstract: Knowledge about the state of the production system is necessary for proper management of a company. A modern company typically uses an ERP (Enterprise Resources Planning) system for management support, but still there is usually a gap between business and manufacturing layers of a company. There is a need to provide solutions allowing data acquisition directly from the production system, analyse this data and display it in a convenient form. Each type of production systems require a different approach to collect data because of variety of objects and conditions. The ability of production data acquisition mostly depends on the level of automation. This paper presents a comparison of methods of data acquisition from different types of manufacturing systems. Methods of data acquisition, from both automated and non-automated manufacturing systems, are described. Automation equipment resources (sensors, actuators, PLC, DCS, CNC, HMI, SCADA) and automatic identification systems (barcodes, RFID, vision systems etc.), as well as communication solutions (fieldbus, wired and wireless networks) and information exchange standards (OPC, MTConnect) are discussed.

Ultralong-offset data acquisition can complement full-waveform inversion and lead to improved subsalt imaging

Abstract: Full-waveform inversion (FWI) has proved itself as a valuable tool for updating and improving the accuracy of subsurface velocity models. For optimum performance, particularly in complex geological environments such as subsalt targets in the Gulf of Mexico (GOM), FWI requires 3D seismic data containing low frequencies and long offsets. For onshore seismic surveys, it is relatively straightforward and cost-effective to record long-offset data; however, for offshore surveys it can incur the additional cost of ocean-bottom cable (OBC) acquisition or multivessel towed-streamer techniques. The recent introduction of dual-coil-shooting multivessel full-azimuth acquisition has provided a highly efficient method of delivering marine 3D seismic data sets with long offsets. Tests using synthetic data and a real GOM dual-coil acquisition data set with full-azimuth distribution and long (up to 14.3-km) offsets demonstrate significant potential for improving the accuracy of velocity models and the reliability of the r...

An Experimental Validation of an Evacuation Model using Data Sets Generated from Two Large Passenger Ships

Abstract: Two evacuation model validation data-sets collected as part of the EU FP7 project SAFEGUARD are presented. The data was collected from a RO-PAX ferry operated by ColorLine (RP1) and a cruise ship operated by Royal Caribbean (CS). The trials were semi-unannounced assembly trials at sea and involved some 1349 and 2500 passengers respectively. The trials took place at an unspecified time however, passengers were aware that on their voyage an assembly exercise would take place. The validation data-sets consist of passenger; response times, starting locations, end locations and arrival times in the assembly stations. The validation data were collected using a novel data acquisition system consisting of ship-mounted beacons, each emitting unique Infra-Red (IR) signals and IR data logging tags worn by each passenger. The results from blind simulations using maritimeEXODUS for these assembly trials are presented and compared with the measured data. Three objective measures are proposed to assess the goodness of fit between the predicted model data and the measured data.