2019
DOI: 10.3390/s19194351
|View full text |Cite
|
Sign up to set email alerts
|

Indoor Positioning on Disparate Commercial Smartphones Using Wi-Fi Access Points Coverage Area

Abstract: The applications of location-based services require precise location information of a user both indoors and outdoors. Global positioning system’s reduced accuracy for indoor environments necessitated the initiation of Indoor Positioning Systems (IPSs). However, the development of an IPS which can determine the user’s position with heterogeneous smartphones in the same fashion is a challenging problem. The performance of Wi-Fi fingerprinting-based IPSs is degraded by many factors including shadowing, absorption… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

1
34
0

Year Published

2019
2019
2023
2023

Publication Types

Select...
9
1

Relationship

1
9

Authors

Journals

citations
Cited by 39 publications
(36 citation statements)
references
References 49 publications
1
34
0
Order By: Relevance
“…The root-mean-square (RMS) positioning error across the three trajectories ranges from 4.28 to 6.65 m, while the overall RMS positioning error, in this case, is 5.92 m, as shown in Table 8. Since these results depend mainly on Wi-Fi fingerprinting, the performance might be affected by the presence of high human mobility in the test area [56]. Additionally, the overall performance of the standalone positioning scenario can be improved by augmenting the solution with other techniques, such as the geomagnetic field anomalies or visual scene recognition [57][58][59][60].…”
Section: Standalone Positioning Resultsmentioning
confidence: 99%
“…The root-mean-square (RMS) positioning error across the three trajectories ranges from 4.28 to 6.65 m, while the overall RMS positioning error, in this case, is 5.92 m, as shown in Table 8. Since these results depend mainly on Wi-Fi fingerprinting, the performance might be affected by the presence of high human mobility in the test area [56]. Additionally, the overall performance of the standalone positioning scenario can be improved by augmenting the solution with other techniques, such as the geomagnetic field anomalies or visual scene recognition [57][58][59][60].…”
Section: Standalone Positioning Resultsmentioning
confidence: 99%
“…RSSI-based Wi-Fi systems provide a median accuracy of ± 0.6 m and suffer from dynamic obstacles interacting with radio propagation [33]. To increase the efficiency and accuracy of these methods, Ashraf et al [34] proposed a Wi-Fi fingerprinting approach that exploits the uniqueness of the Wi-Fi coverage area and overlaps of the coverage areas of several access points (APs). Experimental results demonstrate that the method can mitigate the influence of device diversity and minimize the size of the fingerprint database, thus improving the efficiency of localization [34].…”
Section: Non-camera-based Systemsmentioning
confidence: 99%
“…Indoor mobile agents are widely used in various industries, such as logistics environments [1], military applications [2], automated manufacturing [3], commerce [4], etc. One of the most crucial functions of the indoor mobile agent is to accomplish user-specified tasks.…”
Section: Introductionmentioning
confidence: 99%