WLAN RSS-Based Fingerprinting for Indoor Localization: A Machine Learning Inspired Bag-of-Features Approach.

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Title: WLAN RSS-Based Fingerprinting for Indoor Localization: A Machine Learning Inspired Bag-of-Features Approach.
Authors: Altaf Khattak SB; Smart Systems Engineering Lab, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi Arabia.; Communications Research Center, School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China., Fawad; ACTSENA Research Group, Telecommunication Engineering Department, University of Engineering and Technology Taxila, Punjab 47050, Pakistan., Nasralla MM; Smart Systems Engineering Lab, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi Arabia., Esmail MA; Smart Systems Engineering Lab, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi Arabia., Mostafa H; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia., Jia M; Communications Research Center, School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China.
Source: Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Jul 13; Vol. 22 (14). Date of Electronic Publication: 2022 Jul 13.
Publication Type: Journal Article
Journal Info: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1424-8220
DOI:10.3390/s22145236