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Wi-Fi Indoor Positioning Fingerprint Health Analysis for a Large Scale Deployment

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@article{IJASEIT6837,
   author = {KS Yeo and A Ting and SC Ng and D Chieng and N Anas},
   title = {Wi-Fi Indoor Positioning Fingerprint Health Analysis for a Large Scale Deployment},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {8},
   number = {4-2},
   year = {2018},
   pages = {1411--1416},
   keywords = {indoor location positioning; fingerprint; Wi-Fi},
   abstract = {Indoor positioning systems (IPS) have witnessed continuous improvements over the years. However, large scale commercial deployments remain elusive due to various factors such as high deployment cost and/or lacked of market drivers. Among the state of the art indoor positioning approaches, the Wi-Fi fingerprinting technique in particular, is gaining a lot of attention due its ease of deployment. This is largely due to widespread deployment of WiFi infrastructure and its availability in all existing mobile devices. Although WiFi fingerprinting approach is relatively low cost and fast to deploy, the accuracy of the system tends to deteriorate over time due to WiFi access points (APs) being removed and shifted. In this paper, we carried out a study on such deterioration, which we refer to as fingerprint health analysis on a 2 million square feet shopping mall in South of Kuala Lumpur, Malaysia. We focus our study on APs removal using the actual data collected from the premise. The study reveals the following findings: 1) Based on per location pin analysis, ~50% of APs belong to the mall operator which is a preferred group of APs for fingerprinting. For some location however, the number of operator-managed APs are too few for fingerprinting positioning approach. 2) To maintain mean error distance of ~5 meter, up to 80% of the APs can be removed using the selected positioning algorithms at some locations. At some other locations however, the accuracy will exceed 5m upon >20% of APs being removed. 3) On average, around 40% - 60% of the APs can be removed in random manner in order to maintain the accuracy of ~5m.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=6837},
   doi = {10.18517/ijaseit.8.4-2.6837}
}

EndNote

%A Yeo, KS
%A Ting, A
%A Ng, SC
%A Chieng, D
%A Anas, N
%D 2018
%T Wi-Fi Indoor Positioning Fingerprint Health Analysis for a Large Scale Deployment
%B 2018
%9 indoor location positioning; fingerprint; Wi-Fi
%! Wi-Fi Indoor Positioning Fingerprint Health Analysis for a Large Scale Deployment
%K indoor location positioning; fingerprint; Wi-Fi
%X Indoor positioning systems (IPS) have witnessed continuous improvements over the years. However, large scale commercial deployments remain elusive due to various factors such as high deployment cost and/or lacked of market drivers. Among the state of the art indoor positioning approaches, the Wi-Fi fingerprinting technique in particular, is gaining a lot of attention due its ease of deployment. This is largely due to widespread deployment of WiFi infrastructure and its availability in all existing mobile devices. Although WiFi fingerprinting approach is relatively low cost and fast to deploy, the accuracy of the system tends to deteriorate over time due to WiFi access points (APs) being removed and shifted. In this paper, we carried out a study on such deterioration, which we refer to as fingerprint health analysis on a 2 million square feet shopping mall in South of Kuala Lumpur, Malaysia. We focus our study on APs removal using the actual data collected from the premise. The study reveals the following findings: 1) Based on per location pin analysis, ~50% of APs belong to the mall operator which is a preferred group of APs for fingerprinting. For some location however, the number of operator-managed APs are too few for fingerprinting positioning approach. 2) To maintain mean error distance of ~5 meter, up to 80% of the APs can be removed using the selected positioning algorithms at some locations. At some other locations however, the accuracy will exceed 5m upon >20% of APs being removed. 3) On average, around 40% - 60% of the APs can be removed in random manner in order to maintain the accuracy of ~5m.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=6837
%R doi:10.18517/ijaseit.8.4-2.6837
%J International Journal on Advanced Science, Engineering and Information Technology
%V 8
%N 4-2
%@ 2088-5334

IEEE

KS Yeo,A Ting,SC Ng,D Chieng and N Anas,"Wi-Fi Indoor Positioning Fingerprint Health Analysis for a Large Scale Deployment," International Journal on Advanced Science, Engineering and Information Technology, vol. 8, no. 4-2, pp. 1411-1416, 2018. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.8.4-2.6837.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Yeo, KS
AU  - Ting, A
AU  - Ng, SC
AU  - Chieng, D
AU  - Anas, N
PY  - 2018
TI  - Wi-Fi Indoor Positioning Fingerprint Health Analysis for a Large Scale Deployment
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 8 (2018) No. 4-2
Y2  - 2018
SP  - 1411
EP  - 1416
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - indoor location positioning; fingerprint; Wi-Fi
N2  - Indoor positioning systems (IPS) have witnessed continuous improvements over the years. However, large scale commercial deployments remain elusive due to various factors such as high deployment cost and/or lacked of market drivers. Among the state of the art indoor positioning approaches, the Wi-Fi fingerprinting technique in particular, is gaining a lot of attention due its ease of deployment. This is largely due to widespread deployment of WiFi infrastructure and its availability in all existing mobile devices. Although WiFi fingerprinting approach is relatively low cost and fast to deploy, the accuracy of the system tends to deteriorate over time due to WiFi access points (APs) being removed and shifted. In this paper, we carried out a study on such deterioration, which we refer to as fingerprint health analysis on a 2 million square feet shopping mall in South of Kuala Lumpur, Malaysia. We focus our study on APs removal using the actual data collected from the premise. The study reveals the following findings: 1) Based on per location pin analysis, ~50% of APs belong to the mall operator which is a preferred group of APs for fingerprinting. For some location however, the number of operator-managed APs are too few for fingerprinting positioning approach. 2) To maintain mean error distance of ~5 meter, up to 80% of the APs can be removed using the selected positioning algorithms at some locations. At some other locations however, the accuracy will exceed 5m upon >20% of APs being removed. 3) On average, around 40% - 60% of the APs can be removed in random manner in order to maintain the accuracy of ~5m.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=6837
DO  - 10.18517/ijaseit.8.4-2.6837

RefWorks

RT Journal Article
ID 6837
A1 Yeo, KS
A1 Ting, A
A1 Ng, SC
A1 Chieng, D
A1 Anas, N
T1 Wi-Fi Indoor Positioning Fingerprint Health Analysis for a Large Scale Deployment
JF International Journal on Advanced Science, Engineering and Information Technology
VO 8
IS 4-2
YR 2018
SP 1411
OP 1416
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 indoor location positioning; fingerprint; Wi-Fi
AB Indoor positioning systems (IPS) have witnessed continuous improvements over the years. However, large scale commercial deployments remain elusive due to various factors such as high deployment cost and/or lacked of market drivers. Among the state of the art indoor positioning approaches, the Wi-Fi fingerprinting technique in particular, is gaining a lot of attention due its ease of deployment. This is largely due to widespread deployment of WiFi infrastructure and its availability in all existing mobile devices. Although WiFi fingerprinting approach is relatively low cost and fast to deploy, the accuracy of the system tends to deteriorate over time due to WiFi access points (APs) being removed and shifted. In this paper, we carried out a study on such deterioration, which we refer to as fingerprint health analysis on a 2 million square feet shopping mall in South of Kuala Lumpur, Malaysia. We focus our study on APs removal using the actual data collected from the premise. The study reveals the following findings: 1) Based on per location pin analysis, ~50% of APs belong to the mall operator which is a preferred group of APs for fingerprinting. For some location however, the number of operator-managed APs are too few for fingerprinting positioning approach. 2) To maintain mean error distance of ~5 meter, up to 80% of the APs can be removed using the selected positioning algorithms at some locations. At some other locations however, the accuracy will exceed 5m upon >20% of APs being removed. 3) On average, around 40% - 60% of the APs can be removed in random manner in order to maintain the accuracy of ~5m.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=6837
DO  - 10.18517/ijaseit.8.4-2.6837