Performance Evaluation of Slotted Aloha Anti-Collision Protocol for Mobile RFID Tags Identification using NHPP

Radio Frequency Identification(RFID) plays an important role in identifying objects in evolving field oftheinternet of things (IoT).One important issue relates totheidentification of RFIDs. Despite wide research on this topic, not much work is performedin case when objects with RFID tags are mobile. The paperpresents a simulation-based study, employing non-homogeneous Poisson process to model variable number of tags in an interrogation area,to analyze the performance of the slotted aloha anti-collision protocol in themobile RFID tags identification. It is observedthat the maximum throughput of the protocol reduces as the number of tags increases, however, the throughput usually remains higher than that of aloha protocol in static environment.These results will help in developing better probabilistic anti-collision protocols for dynamic environment in future.

Large-Scale Particle Image Velocimetry for Estimating Vena-Contracta Width for Flow in Contracted Open Channels

This paper presents the findings of a flume study using large-scale particle velocimetry (LSPIV) to estimate the top-width of the vena contracta formed by an approach open-channel flow entering a contraction of the channel. LSPIV is an image-based method that non-invasively measures two-dimensional instantaneous free-surface velocities of water flow using video equipment. The experiments investigated the requisite dimensions of two essential LSPIV components—search area and interrogation area– to establish the optimum range of these components for use in LSPIV application to contractions of open-channel flows. Of practical concern (e.g., bridge hydraulics) is flow contraction and contraction scour that can occur in the vena contracta region. The study showed that optimum values for the search area (SA) and interrogation area (IA) were 10 and 60 pixels, respectively. Also, the study produced a curve indicating a trend for vena-contracta width narrowing with a variable ratio of approach-channel and contracted-channel widths and varying bed shear stress of approach flow.

On the Uncertainty of the Image Velocimetry Method Parameters

Image velocimetry is a popular remote sensing method mainly because of the very modest cost of the necessary equipment. However, image velocimetry methods employ parameters that require high expertise to select appropriate values in order to obtain accurate surface flow velocity estimations. This introduces considerations regarding the subjectivity introduced in the definition of the parameter values and its impact on the estimated surface velocity. Alternatively, a statistical approach can be employed instead of directly selecting a value for each image velocimetry parameter. First, probability distribution should be defined for each model parameter, and then Monte Carlo simulations should be employed. In this paper, we demonstrate how this statistical approach can be used to simultaneously produce the confidence intervals of the estimated surface velocity, reduce the uncertainty of some parameters (more specifically, the size of the interrogation area), and reduce the subjectivity. Since image velocimetry algorithms are CPU-intensive, an alternative random number generator that allows obtaining the confidence intervals with a limited number of iterations is suggested. The case study indicated that if the statistical approach is applied diligently, one can achieve the previously mentioned threefold objective.

Efficiency of a Digital Particle Image Velocimetry (DPIV) Method for Monitoring the Surface Velocity of Hyper-Concentrated Flows

Digital particle image velocimetry records high resolution images and allows the identification of the position of points in different time instants. This paper explores the efficiency of the digital image-technique for remote monitoring of surface velocity and discharge measurement in hyper-concentrated flow by the way of laboratory experiment. One of the challenges in the application of the image-technique is the evaluation of the error in estimating surface velocity. The error quantification is complex because it depends on many factors characterizing either the experimental conditions or/and the processing algorithm. In the present work, attention is devoted to the estimation error due either to the acquisition time or to the size of the sub-images (interrogation areas) to be correlated. The analysis is conducted with the aid of data collected in a scale laboratory flume constructed at the Hydraulic laboratory of the Department of Civil, Environmental, Aerospace and of Materials Engineering (DICAM)—University of Palermo (Italy) and the image processing is carried out by the help of the PivLab algorithm in Matlab. The obtained results confirm that the number of frames used in processing procedure strongly affects the values of surface velocity; the estimation error decreases as the number of frames increases. The size of the interrogation area also exerts an important role in the flow velocity estimation. For the examined case, a reduction of the size of the interrogation area of one half compared to its original size has allowed us to obtain low values of the velocity estimation error. Results also demonstrate the ability of the digital image-technique to estimate the discharge at given cross-sections. The values of the discharge estimated by applying the digital image-technique downstream of the inflow sections by using the aforementioned size of the interrogation area compares well with those measured.

PRIMARY PEAK RATIO CORRELATION TO THE MEASUREMENT ACCURACY OF PIV METHOD

An estimation of a measurement accuracy at each measured point is crucial regarding the applicability of results of the measurements. The aim of this work is to determine the correlation between individual metrics and the measurement accuracy by using corrected metrics of the correlation plane. This work is based on defining a corrected metric using known metrics corrected by the displacement measured in the last iteration, the number of the particles and the velocity gradient inside the interrogation area. The resulting tests are performed using conventional synthetic tests. The discovered dependencies between individual corrected metrics are subsequently approximated in order to determine the measurement accuracy. And, finally, the most suitable variant for the determination of the accuracy of the measurement by the particle image velocimetry method is specified.

Automation Using Matrix Switch for Piezoelectric Actuator/Sensor Based Structural Health Monitoring

The implementation of the switch is the stepstone of a fully automated structural health monitoring (SHM) System. This paper attempted to tackle the hardware connectivity issues when dense transducer arrays present in the system with the switch that features the matrix topology. The program that controls the instruments and automates the data acquisition for SHM system was developed in LabVIEW, in which a scanning approach that sensorises the interrogation area and a hybrid programming technique are employed. Through interfacing with a top-level GUI of the program, it is easy to be controlled and employed. The solution showed a significant reduction in testing time comparing that with manual switch operation and a weight-saving solution as a minimum number of shielded cable needed. In addition, because only one channel each from the signal generator and digitiser is required, it is less demanding on the specification of the instruments. The prototype of the current system can be scaled up for testing on a larger structure due to its modular nature in both PXI express system and software design.