A passive energy-based method for footstep impact localization, using an underfloor accelerometer sensor network with Kalman filtering

2020 ◽  
Vol 26 (11-12) ◽  
pp. 941-951 ◽  
Author(s):  
Sa’ed Alajlouni ◽  
Pablo Tarazaga
Keyword(s):  
Sensor Network ◽  
Kalman Filtering ◽  
Sampling Rate ◽  
Data Sampling ◽  
Accelerometer Sensor ◽  
Localization Accuracy ◽  
New Energy ◽  
Data Sampling Rate ◽  
Floor Vibration ◽  
Impact Localization

An underfloor accelerometer sensor network can be used to track occupants in an indoor environment using measurements of floor vibration induced by occupant footsteps. To achieve occupant tracking, each footstep impact location must first be estimated. This paper proposes a new energy-based algorithm for footstep impact localization. Compared to existing energy-based algorithms, the new algorithm achieves higher localization accuracy and removes a previously required calibration step (removal of the need to estimate floor-dependent parameters). Furthermore, the algorithm uses a much smaller data sampling rate compared to time of flight/arrival localization methods, which greatly reduces data and data-processing time. The new algorithm is a two-step location estimator: the first step is a coarse location estimate, with the second step as a fine location search through a nonlinear minimization problem. The performance of the proposed algorithm is evaluated using a single occupant walking experiment on an instrumented floor inside an operational smart building. This paper also demonstrates that higher localization accuracy is obtained using an additional Kalman filtering scheme.

scholarly journals Effect of Sampling Rate on Photovoltaic Self-Consumption in Load Shifting Simulations

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5393
Author(s):  
Philippe Voinov ◽  
Patrick Huber ◽  
Alberto Calatroni ◽  
Andreas Rumsch ◽  
Andrew Paice
Keyword(s):  
Sampling Rate ◽  
Smart Meter ◽  
Data Sampling ◽  
Load Shifting ◽  
Consumption Data ◽  
Data Sampling Rate ◽  
Potential Improvement ◽  
Using Data ◽  
The Uk ◽  
The Impact

Grid-connected photovoltaic (PV) capacity is increasing and is currently estimated to account for 3.0% of worldwide energy generation. One strategy to balance fluctuating PV power is to incentivize self-consumption by shifting certain loads. The potential improvement in the amount of self-consumption is usually estimated using smart meter and PV production data. Smart meter data are usually available only at sampling frequences far below the Nyquist limit. In this paper we investigate how this insufficient sampling rate affects the estimated self-consumption potential of shiftable household appliances (washing machines, tumble dryers and dishwashers). We base our analyses on measured consumption data from 16 households in the UK and corresponding PV data. We found that the simulated results have a marked dependence on the data sampling rate. The amount of self-consumed energy estimated with data sampled every 10 min was overestimated by 30–40% compared to estimations using data with 1 min sampling rate. We therefore recommend to take this factor into account when making predictions on the impact of appliance load shifting on the rate of self-consumption.

Impact Analysis of Guidance Instrument Error Separation Accuracy on Sampling Rate of Inertial Navigation Equipment

2013 ◽  
Vol 341-342 ◽  
pp. 880-886
Author(s):  
Wen Jun Wang ◽  
Xiao Jun Duan ◽  
Ju Bo Zhu
Keyword(s):  
Impact Analysis ◽  
Sampling Rate ◽  
Inertial Navigation ◽  
Optimal Sampling ◽  
Data Sampling ◽  
Instrument Error ◽  
Error Separation ◽  
Data Sampling Rate ◽  
Simulation Results ◽  
Navigation Equipment

Based on the linear model of guidance instrument error separation, study on the separation accuracy affected by data sampling rate of inertial navigation equipment. First, theoretically proved that the higher data sampling rate is, the higher separation accuracy we can get. Second, a method for determining the optimal sampling rate is presented, whose idea is from the model itself. At last, the simulation results can verify the above two conclusions.

Effects of Data Sampling Rate on Pattern Recognition Analysis of FT-IR Interferograms

1992 ◽  
Vol 46 (1) ◽  
pp. 49-59 ◽  
Author(s):  
Gary W. Small ◽  
Scott E. Carpenter
Keyword(s):  
Pattern Recognition ◽  
Sampling Rate ◽  
Data Sampling ◽  
Monitoring Applications ◽  
Data Sampling Rate ◽  
Ft Ir ◽  
Pattern Recognition Analysis ◽  
Improved Performance ◽  
Mixture Samples ◽  
The Impact

Fourier transform infrared (FT-IR) data of pure and mixture samples of benzene and nitrobenzene are used to investigate and improve methods for interferogram-based qualitative analyses. For use in dedicated monitoring applications, the methodology employed is based on the application of pattern recognition analysis to short, digitally filtered interferogram segments. In the work described here, the impact of the interferogram data sampling rate on the analysis is studied. The results of this study indicate that optimal pattern recognition prediction performance is achieved by use of linear discriminants developed from faster sampled interferogram data. These findings suggest that improved performance can be obtained in FT-IR monitoring applications through the use of spectrometer designs based on a decreased interferogram scan length, coupled with faster sampling electronics.

scholarly journals 094 Towards objective testing in parkinson’s disease: a systematic review of the literature looking at assessment of postural sway

2019 ◽  
Vol 90 (e7) ◽  
pp. A30.2-A30
Author(s):  
Wenbo Ge ◽  
Deborah Apthorp ◽  
Christian J Lueck ◽  
Hanna Suominen
Keyword(s):  
Systematic Review ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Postural Sway ◽  
Sampling Rate ◽  
Objective Measure ◽  
Data Sampling ◽  
Data Sampling Rate ◽  
Objective Marker

IntroductionParkinson’s Disease (PD) is associated with increased mortality and reduced quality of life. There is currently no accurate objective measure for use in diagnosis or assessment of severity. Analysis of postural sway may help in this regard. This systematic review aimed to assess the effectiveness of the various features currently used to analyse postural sway.MethodsFive databases were searched for articles that examined postural sway in both PD patients and controls. An effect size (ES) was derived for every feature reported in each article. The most effective features and feature-families were determined, along with the influence on these measures of data sampling rate and experimental condition.Results441 papers were initially retrieved, of which 31 met the requirements for analysis. The most commonly-used features were not the most effective (e.g. PathLength had an ES of 0.47 while TotalEnergy had an ES of 1.78). Decreased sampling rate was associated with decreased ES (e.g. ES of PathLength lowered from 1.12 at 100 Hz to 0.40 at 10 Hz). Being off medication was associated with a larger ES (e.g. ES of PathLength was 0.21 on medication and 0.83 off medication).ConclusionsSome measures of postural sway are better able to distinguish PD patients from controls than others. ES is enhanced by using a higher sampling rate and studying patients off medication. These results will inform future studies looking at postural sway in PD and contribute to the aim of finding an objective marker of the disease.

A new fast and calibration-free method for footstep impact localization in an instrumented floor

2019 ◽  
Vol 25 (10) ◽  
pp. 1629-1638 ◽  
Author(s):  
Sa'ed Alajlouni ◽  
Pablo Tarazaga
Keyword(s):  
Homogeneous Material ◽  
Accelerometer Sensor ◽  
Additional Advantage ◽  
Localization Accuracy ◽  
Smart Building ◽  
Current Localization ◽  
Dispersion Problem ◽  
Impact Localization ◽  
Location Estimate ◽  
High Uncertainty

Impact localization in a floor is complicated due to the dispersion-caused distortion of the generated floor waves. Current localization methods that try to overcome the dispersion problem are computationally expensive, taking in some cases 2 seconds to yield a single footstep location estimate. If an accelerometer sensor network is utilized to localize footsteps, and consequently track an occupant's path, then there is a need for computationally fast algorithms that are able to keep up with the walking (or running) impact frequency; therefore, in this paper, a practical algorithm is proposed for footstep impact localization in an instrumented floor. The proposed algorithm has promising sub-meter localization accuracy and is computationally fast. In addition, the algorithm does not require estimation of floor-dependent parameters, which is an additional advantage since estimating floor-dependent parameters in a floor will have relatively high uncertainty as the floor cannot be treated as an isotropic/homogeneous material. The proposed algorithm is evaluated using simulations and an experiment in an operational smart building.

Effects of data sampling rate on image quality in fan-beam CT system

1985 ◽  
Vol 16 (2) ◽  
pp. 77-84
Author(s):  
Aklra Iwata ◽  
Nobutoshi Yamagishi ◽  
Nobuo Suzumura ◽  
Isao Horiba
Keyword(s):  
Image Quality ◽  
Sampling Rate ◽  
Data Sampling ◽  
Data Sampling Rate ◽  
Ct System

CALCULATION OF ENGINE PARAMETERS USING RECONFIGURABLE HARDWARE

2014 ◽  
Vol 11 (supp01) ◽  
pp. 1344011
Author(s):  
J. BANKS ◽  
N. A. KELSON ◽  
H. MACINTOSH ◽  
M. DAGG ◽  
R. HAYWARD ◽  
...  
Keyword(s):  
Real Time ◽  
Combustion Engine ◽  
Sampling Rate ◽  
Reconfigurable Hardware ◽  
Data Sampling ◽  
Real Time Processing ◽  
Calculation Of Parameters ◽  
Field Programmable ◽  
Data Sampling Rate ◽  
Time Calculation

The feasibility of real-time calculation of parameters for an internal combustion engine via reconfigurable hardware implementation is investigated as an alternative to software computation. A detailed in-hardware field programmable gate array (FPGA)-based design is developed and evaluated using input crank angle and in-cylinder pressure data from fully instrumented diesel engines in the QUT Biofuel Engine Research Facility (BERF). Results indicate the feasibility of employing a hardware-based implementation for real-time processing for speeds comparable to the data sampling rate currently used in the facility, with acceptably low level of discrepancies between hardware and software-based calculation of key engine parameters.

scholarly journals Impact Localization Method for Composite Plate Based on Low Sampling Rate Embedded Fiber Bragg Grating Sensors

2017 ◽  
Vol 2017 ◽  
pp. 1-9
Author(s):  
Zhuo Pang ◽  
Mei Yuan ◽  
Hao Song ◽  
Zongxia Jiao
Keyword(s):  
Fiber Bragg Grating ◽  
Sampling Rate ◽  
Classification Model ◽  
Support Vector ◽  
Bragg Grating ◽  
Localization Algorithm ◽  
Experimental Conditions ◽  
Localization Accuracy ◽  
The Impact ◽  
Impact Localization

Fiber Bragg Grating (FBG) sensors have been increasingly used in the field of Structural Health Monitoring (SHM) in recent years. In this paper, we proposed an impact localization algorithm based on the Empirical Mode Decomposition (EMD) and Particle Swarm Optimization-Support Vector Machine (PSO-SVM) to achieve better localization accuracy for the FBG-embedded plate. In our method, EMD is used to extract the features of FBG signals, and PSO-SVM is then applied to automatically train a classification model for the impact localization. Meanwhile, an impact monitoring system for the FBG-embedded composites has been established to actually validate our algorithm. Moreover, the relationship between the localization accuracy and the distance from impact to the nearest sensor has also been studied. Results suggest that the localization accuracy keeps increasing and is satisfactory, ranging from 93.89% to 97.14%, on our experimental conditions with the decrease of the distance. This article reports an effective and easy-implementing method for FBG signal processing on SHM systems of the composites.

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