Conference
New Machine Learning Hybrid Models to Lower Position Errors for Bluetooth-Based Indoor Localizations
Abstract
In recent times, there has been a significant development of critical IoT-based applications in the field of indoor localization (e.g., locating an asset or person). The utilization of Machine Learning (ML) algorithms to enhance accuracy in the presence of interference has generated considerable interest among researchers in this domain. This research paper introduces two hybrid models, namely the Asymmetric and Symmetric Line-Shifting hybrid …
Authors
Salti TE; Sykes ER; Cheung JC-C; Dalal K; Tauhid A; Zou X
Pagination
pp. 25-34
Publisher
Association for Computing Machinery (ACM)
Publication Date
October 30, 2023
DOI
10.1145/3616390.3618289
Name of conference
Proceedings of the Int'l ACM Symposium on Mobility Management and Wireless Access