Sliding Window, Hierarchical Classification, Regression, and Genetic Algorithm for RFID Indoor Positioning Systems

Several surveys in the Indoor Positioning System (IPS) use the Radio Signal Strength Indicator (RSSI) to locate target objects. However, RSSI suffers significantly from the multipath phenomenon and other environmental factors such as the absence of the field of view, reflective materials, excessive...

Full description

Saved in:
Bibliographic Details
Published in:Expert systems with applications 2024-03, Vol.238, p.122298, Article 122298
Main Authors: Gomes, Eduardo Luis, Fonseca, Mauro Sergio Pereira, Lazzaretti, André Eugenio, Munaretto, Anelise, Guerber, Carlos Rafael
Format: Article
Language:English
Subjects:
Genetic Algorithm
Hierarchical Classification
Indoor Positioning System
Random Forest Regressor
RFID
Sliding Window
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Several surveys in the Indoor Positioning System (IPS) use the Radio Signal Strength Indicator (RSSI) to locate target objects. However, RSSI suffers significantly from the multipath phenomenon and other environmental factors such as the absence of the field of view, reflective materials, excessive obstacles, and a high density of objects. To overcome such problems, we propose three new IPS approaches using Radio Frequency Identification (RFID) technology and the collaborative use of Sliding Window, Hierarchical Classification, Random Forest Regressor, and Genetic Algorithm. We tested the new approaches on three datasets obtained in different environments and compared them with two state-of-the-art IPS approaches (Landmarc and SVR-Landmarc). One of the main results got was a precision of 4.82 cm in an environment with 7,000 target tags, reducing by up to 92.91% the average error w.r.t. other IPS approaches presented in the literature, including more complex indoor scenarios. •The problem of interference in radiofrequency waves in RFID systems is addressed.•The sliding window to smooth out interference from RFID readings is introduced.•Three new RFID indoor positioning systems are proposed.•An RFID dataset for indoor location is made available.•A complete experimental analysis and comprehensive comparison are provided.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2023.122298