Record Details

Conventional system to deep learning based indoor positioning system

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Title Conventional system to deep learning based indoor positioning system
 
Creator Sharma, Shiva
Kumar, Naresh
Kaur, Manjit
 
Subject Artificial intelligence (AI)
Deep learning (DL)
Global positioning system (GPS)
Indoor positioning (IP)
Reliability
Sensor fusion (SF)
 
Description 7-24
This review article presents the key fundamentals of indoor positioning system (IPS) and its progressing footprints. The
need of IPS and work done with methodology adopted to implement IPS for various applications have been discussed. The
evolution from conventional to deep learning (DL) has been presented, addressing various challenges existing in
conventional IPS like poor localization, improper accuracy, non-line-of-sight problems, instability of signal due to fading,
requirements of large infrastructure, data-set and labour, high cost, and their existing solutions have been disclosed. Further
in order to compute the indoor positioning with acute precision various advanced positioning technologies including sensor
fusion, artificial Intelligence (AI), and hybrid technologies have been explored. The issues and challenges existing in current
IPS technology have been presented and future insights to work in this direction have also been provided.
 
Date 2024-04-02T09:57:23Z
2024-04-02T09:57:23Z
2024-04
 
Type Article
 
Identifier 0975-1017 (Online); 0971-4588 (Print)
http://nopr.niscpr.res.in/handle/123456789/63678
https://doi.org/10.56042/ijems.v31i1.5183
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source IJEMS Vol.31(1) February