Evidence map›Paper›PMID 31597391›Full record

ArticleSensors (Basel, Switzerland)2019

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

Imran Ashraf, Soojung Hur, Yongwan Park

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Smartphone Sensors for Indoor Positioning.Sensors (Basel, Switzerland) · 2023
    Article
  5. An Indoor Location-Based Augmented Reality Framework.Sensors (Basel, Switzerland) · 2023
    Article
  6. Article
  7. Article
  8. An RSS Transform-Based WKNN for Indoor Positioning.Sensors (Basel, Switzerland) · 2021
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Imran AshrafDepartment of Information & Communication Engineering, Yeungnam University, Gyeongbuk, Gyeongsan-si 38541, Korea. ashrafimran@live.com.ORCID 0000-0002-8271-6496
Soojung HurDepartment of Information & Communication Engineering, Yeungnam University, Gyeongbuk, Gyeongsan-si 38541, Korea. sjheo@ynu.ac.kr.
Yongwan ParkDepartment of Information & Communication Engineering, Yeungnam University, Gyeongbuk, Gyeongsan-si 38541, Korea. ywpark@yu.ac.kr.

Funding

Ministry of Science, ICT (MSIT) Korea, under the Information Technology Research Center IITP-2018-2016-0-00313National Research Foundation of Korea (NRF) 2017R1E1A1A01074345
6 · The paper itself

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, and interference caused by obstacles, human mobility, and body loss. Moreover, the use of various smartphones and different orientations of the very same smartphone can limit its positioning accuracy as well. As Wi-Fi fingerprinting is based on Received Signal Strength (RSS) vector, it is prone to dynamic intrinsic limitations of radio propagation, including changes over time, and far away locations having similar RSS vector. This article presents a Wi-Fi fingerprinting approach that exploits Wi-Fi Access Points (APs) coverage area and does not utilize the RSS vector. Using the concepts of APs coverage area uniqueness and coverage area overlap, the proposed approach calculates the user's current position with the help of APs' intersection area. The experimental results demonstrate that the device dependency can be mitigated by making the fingerprinting database with the proposed approach. The experiments performed at a public place proves that positioning accuracy can also be increased because the proposed approach performs well in dynamic environments with human mobility. The impact of human body loss is studied as well.

Indexed as

access points coverage areaindoor positioningreceived signal strengthsmartphone heterogeneityWi-Fi fingerprinting

Identifiers

PMID31597391
PMCPMC6806077

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.