Spatial Region Estimation for Autonomous CoT Clustering Using Hidden Markov Model

This paper proposes a hierarchical dual filtering (HDF) algorithm to estimate the spatial region between a Cloud of Things (CoT) gateway and an Internet of Things (IoT) device. The accuracy of the spatial region estimation is important for autonomous CoT clustering. We conduct spatial region estimat...

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Main Authors: Joon‐young Jung, Okgee Min
Format: Article
Language:English
Published: Electronics and Telecommunications Research Institute (ETRI) 2018-02-01
Series:ETRI Journal
Subjects:
Online Access:https://doi.org/10.4218/etrij.18.0117.0142
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author Joon‐young Jung
Okgee Min
author_facet Joon‐young Jung
Okgee Min
author_sort Joon‐young Jung
collection DOAJ
description This paper proposes a hierarchical dual filtering (HDF) algorithm to estimate the spatial region between a Cloud of Things (CoT) gateway and an Internet of Things (IoT) device. The accuracy of the spatial region estimation is important for autonomous CoT clustering. We conduct spatial region estimation using a hidden Markov model (HMM) with a raw Bluetooth received signal strength indicator (RSSI). However, the accuracy of the region estimation using the validation data is only 53.8%. To increase the accuracy of the spatial region estimation, the HDF algorithm removes the high‐frequency signals hierarchically, and alters the parameters according to whether the IoT device moves. The accuracy of spatial region estimation using a raw RSSI, Kalman filter, and HDF are compared to evaluate the effectiveness of the HDF algorithm. The success rate and root mean square error (RMSE) of all regions are 0.538, 0.622, and 0.75, and 0.997, 0.812, and 0.5 when raw RSSI, a Kalman filter, and HDF are used, respectively. The HDF algorithm attains the best results in terms of the success rate and RMSE of spatial region estimation using HMM.
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spelling doaj.art-6cf24aa723ac45dc97dc16f245e4b1182022-12-21T19:26:22ZengElectronics and Telecommunications Research Institute (ETRI)ETRI Journal1225-64632233-73262018-02-0140112213210.4218/etrij.18.0117.014210.4218/etrij.18.0117.0142Spatial Region Estimation for Autonomous CoT Clustering Using Hidden Markov ModelJoon‐young JungOkgee MinThis paper proposes a hierarchical dual filtering (HDF) algorithm to estimate the spatial region between a Cloud of Things (CoT) gateway and an Internet of Things (IoT) device. The accuracy of the spatial region estimation is important for autonomous CoT clustering. We conduct spatial region estimation using a hidden Markov model (HMM) with a raw Bluetooth received signal strength indicator (RSSI). However, the accuracy of the region estimation using the validation data is only 53.8%. To increase the accuracy of the spatial region estimation, the HDF algorithm removes the high‐frequency signals hierarchically, and alters the parameters according to whether the IoT device moves. The accuracy of spatial region estimation using a raw RSSI, Kalman filter, and HDF are compared to evaluate the effectiveness of the HDF algorithm. The success rate and root mean square error (RMSE) of all regions are 0.538, 0.622, and 0.75, and 0.997, 0.812, and 0.5 when raw RSSI, a Kalman filter, and HDF are used, respectively. The HDF algorithm attains the best results in terms of the success rate and RMSE of spatial region estimation using HMM.https://doi.org/10.4218/etrij.18.0117.0142CoT clusteringHidden Markov modelHierarchical dual filteringRegion estimation
spellingShingle Joon‐young Jung
Okgee Min
Spatial Region Estimation for Autonomous CoT Clustering Using Hidden Markov Model
ETRI Journal
CoT clustering
Hidden Markov model
Hierarchical dual filtering
Region estimation
title Spatial Region Estimation for Autonomous CoT Clustering Using Hidden Markov Model
title_full Spatial Region Estimation for Autonomous CoT Clustering Using Hidden Markov Model
title_fullStr Spatial Region Estimation for Autonomous CoT Clustering Using Hidden Markov Model
title_full_unstemmed Spatial Region Estimation for Autonomous CoT Clustering Using Hidden Markov Model
title_short Spatial Region Estimation for Autonomous CoT Clustering Using Hidden Markov Model
title_sort spatial region estimation for autonomous cot clustering using hidden markov model
topic CoT clustering
Hidden Markov model
Hierarchical dual filtering
Region estimation
url https://doi.org/10.4218/etrij.18.0117.0142
work_keys_str_mv AT joonyoungjung spatialregionestimationforautonomouscotclusteringusinghiddenmarkovmodel
AT okgeemin spatialregionestimationforautonomouscotclusteringusinghiddenmarkovmodel