A novel device-free Wi-Fi indoor localization using a convolutional neural network based on residual attention.

ABSTRACT: These days, location-based services, or LBS, are used for various consumer applications, including indoor localization. Due to the ease with which Wi-Fi can be accessed in various interior settings, there has been increasing interest in Wi-Fi-based indoor localisation. Deep learning in indoor localisation systems that use channel state information (CSI) fingerprinting has seen widespread adoption. Usually, these systems comprise two primary components: a positioning network and a tracking system. The positioning network is responsible for learning the planning from high-dimensional CSI to physical positions, and the following system uses historical CSI to decrease positioning error. This work presents a novel localization method that combines high accuracy and generalizability. However, ex

SUBMITTER: Maashi M 

PROVIDER: S-EPMC11784888 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature