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Anomaly Detection Based on Generalized Gaussian Distribution approach for Ultra-Wideband (UWB) Indoor Positioning System
[article]
2021
arXiv
pre-print
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This paper focuses on employing an anomaly detection approach based on Gaussian Distribution (GD) and Generalized Gaussian Distribution (GGD) algorithms to detect and identify the NLoS components. ...
However, the UWB system still faces several technical challenges in practice, one of which is Non-Line-of-Sight (NLoS) signal propagation. ...
In [19] , [20] , the authors proposed Least Square-Support Vector Machine (LS-SVM) algorithm to distinguish between the Line of Sight (LoS) and NLoS components. ...
arXiv:2108.10210v1
fatcat:p7lp64bu6nguddh5apgty4w3nu
A Seamless Navigation System and Applications for Autonomous Vehicles Using a Tightly Coupled GNSS/UWB/INS/Map Integration Scheme
2021
Remote Sensing
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Finally, an improved adaptive robust extended Kalman filter (AREKF) algorithm based on a TC integrated single-frequency multi-GNSS-TC RTK/UWB/INS/map system is studied to provide continuous, reliable, ...
UWB non-line-of-sight (NLOS) errors. ...
[19] conducted research on the seamless positioning of indoor mobile robots and proposed an algorithm using the EKF and the least squares support vector machine (LS-SVM). ...
doi:10.3390/rs14010027
fatcat:npm533asezej5i4lxh2wt3gnwm
Self-Corrective Sensor Fusion for Drone Positioning in Indoor Facilities
2020
IEEE Access
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It corrects visual odometer readings based on filtered and clustered Ultra-Wide Band (UWB) data, as an alternative to direct Kalman fusion. ...
It has three method components: independent Kalman filtering, data association by means of stream clustering and mutual correction of sensor readings based on the generation of cumulative correction vectors ...
Coordinate (0, 0, 0) is the precise location of the first anchor, which has always the lowest identifier. ...
doi:10.1109/access.2020.3048194
fatcat:bcmg5p7b7ngonm5slfuzaa6h4m
Tracking and analysing social interactions in dairy cattle with real-time locating system and machine learning
2021
Journal of systems architecture
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The real-time locating system based on Ultra-wideband technology reached an accuracy with mean error 0.39 m and standard deviation 0.62 m. ...
Detections of the dairy cows' negative and positive interactions were performed on foreground video stream using a Long-term Recurrent Convolution Networks model. ...
Real-time location module We designed an UWB RTLS sensor tag based on the Decawave DWM1000 module. ...
doi:10.1016/j.sysarc.2021.102139
fatcat:sujcvy56hzgpfmepngr5vkkepa
Machine Learning Based Localization in Large-Scale Wireless Sensor Networks
2018
Sensors
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Our results have revealed interesting insights while using the multivariate regression model and support vector machine (SVM) regression model with radial basis function (RBF) kernel. ...
Machine learning based localizing algorithms for large wireless sensor networks do not function in an iterative manner. ...
Support Vector Machine Regression Model One of the most popular machine learning algorithms is named support vector machines (SVM), which is mostly used for classification. ...
doi:10.3390/s18124179
pmid:30487457
fatcat:zmc4yglclffrjin2bjwcxkjrpe
Physiological and Behavior Monitoring Systems for Smart Healthcare Environments: A Review
2020
Sensors
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The machine learning methods that are most used in the literature for activity recognition and body motion analysis are also referred. ...
The implementation of Internet of Things (IoT) in the healthcare ecosystem has been one of the best solutions to address these challenges and therefore to prevent and diagnose possible health impairments ...
Other drawbacks include the need of having at least three receivers to receive the signals from the tags, a higher level of complexity on its installation, since UWB reader locations need to be carefully ...
doi:10.3390/s20082186
pmid:32290639
fatcat:aj73magczbeivcetqbcbyvxcyu
IPIN 2018 Ninth International Conference on Indoor Positioning and Indoor Navigation
2018
2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN)
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These features are used as inputs for conventional regression techniques such as Support Vector Machine and K-Nearest Neighbors. ...
Recently a number of approaches based on machine learning (ML) aim to address such issues. ...
The state-of-the-art in device-free localization systems based on RF-measurements is fingerprinting. ...
doi:10.1109/ipin.2018.8533737
fatcat:rv5zjhjytjaijcqgvvvpmbfjfa
Multimodal Approaches for Indoor Localization for Ambient Assisted Living in Smart Homes
2021
Information
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Finally, it presents a comprehensive comparative study that includes Random Forest, Artificial Neural Network, Decision Tree, Support Vector Machine, k-NN, Gradient Boosted Trees, Deep Learning, and Linear ...
location in a specific 'activity-based zone' during Activities of Daily Living. ...
This data can be found at: https://doi.org/10.17632/sy3kcttdtx.1 and https://www.kaggle.com/liwste/indoor-positioning, accessed on 13 February 2021. ...
doi:10.3390/info12030114
fatcat:ankfyi77inhqxg22fra3rcgzxq
Optimizing Node Localization in Wireless Sensor Networks Based on Received Signal Strength Indicator
2019
IEEE Access
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In order to improve the precision of inside localization and optimize the allocation of node resources in wireless sensor networks (WSNs), an equal-arc trilateral localization algorithm based on received ...
square beacon model, the traditional equilateral triangle beacon model, and the improved equilateral triangle beacon model. ...
, compared with the traditional grid search algorithm optimization support vector machine. ...
doi:10.1109/access.2019.2920279
fatcat:54a3dgbh2rfe3ej56jqgvblw2m
Indoor Localization System Using Fingerprinting and Novelty Detection for Evaluation of Confidence
2022
Future Internet
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Fingerprinting is one of the most known solutions for indoor localization. It is based on the Received Signal Strength (RSS) of packets transmitted among mobile devices and anchor nodes. ...
This instability and noise often cause the system to indicate a location that it is not quite sure is correct, although it is the most likely based on the calculations. ...
The supervised learning method includes support vector machine (SVM), kNN, and random forest (RF) classifiers. ...
doi:10.3390/fi14020051
fatcat:lpksn73vgng4fjmzr3mnlohxdq
A DEEP LEARNING MODEL IMPLEMENTATION BASED ON RSSI FINGERPRINTING FOR LORA-BASED INDOOR LOCALIZATION
2021
EUREKA Physics and Engineering
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Based on the test results, DeepFi-LoRaIn Technique can be a solution to cope with changing environmental conditions in indoor localization ...
The variety of approaches to solving accuracy problems continues to improve as the need for indoor localization applications increases. ...
Acknowledgement We thank Ministry of Research and Higher Education of Republic of Indonesia for financial support for this research under the PDD Grant number NKB-423/UN2.RST/HKP.05.00/2020. ...
doi:10.21303/2461-4262.2021.001620
fatcat:hawn2mjwzvbyjo66k6cjajblva
Analysis of asset location data to support decisions in production management and control
2020
Procedia CIRP
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the location of various equipment on the shop-floor in near real time. ...
the location of various equipment on the shop-floor in near real time. ...
by the GINOP-2.3.2-15-2016-00002 grant on an "Industry 4.0 research and innovation center of excellence". ...
doi:10.1016/j.procir.2020.05.035
fatcat:vta5rcyriffvdpumovmt7sjp3m
A Review of Wearable Technologies for Elderly Care that Can Accurately Track Indoor Position, Recognize Physical Activities and Monitor Vital Signs in Real Time
2017
Sensors
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These technologies are categorized into three types: indoor positioning, activity recognition and real time vital sign monitoring. ...
Recently, advances in wearable and sensor technologies have improved the prospects of these service systems for assisting elderly people. ...
Besides, we thank the anonymous reviewers for their comments which helped improve this paper to its present form. This work was supported in part by CTBU, HSN, and NUDT. ...
doi:10.3390/s17020341
pmid:28208620
pmcid:PMC5336038
fatcat:h4cxt3ag4rabpk7qe4e3mvp7ku
Indoor NLOS Positioning System Based on Enhanced CSI Feature with Intrusion Adaptability
2020
Sensors
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In addition, binary and improved multiple support vector classification (SVC) models are established to realize NLOS intrusion detection and high-discrimination fingerprint localization, respectively. ...
In this paper, we propose an enhanced CSI-based indoor positioning system with pre-intrusion detection suitable for NLOS scenarios (C-InP). ...
the support vector machine. ...
doi:10.3390/s20041211
pmid:32098411
pmcid:PMC7070768
fatcat:fby3tr7ebbc6za6jaogwvywwnu
A Cooperative Machine Learning Approach for Pedestrian Navigation in Indoor IoT
2019
Sensors
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To improve the location accuracy, this paper proposes a novel cooperative system to estimate the direction of motion based on a machine learning approach for perturbation detection and filtering, combined ...
A first algorithm filters out perturbed magnetometer measurements based on a-priori information on the Earth's magnetic field. ...
The following classification algorithms are evaluated using the software Weka [56] : Support Vector Machine, Multi Layer Perceptron, Decision Tree, 3-Nearest Neighbour, Logistic Regression and Naïve Bayes ...
doi:10.3390/s19214609
fatcat:abiechapgbhqxgzur6pgp3drfi
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