Ray‐tracing assisted fingerprinting for localization in IoT Health 4.0

Abstract

The Internet of Things (IoT) can help healthcare companies establish Ambient Assisted Living (AAL). It permits innovative solutions to a well‐known problem, notably the real‐time localization and monitoring of patients and clinicians. Yet, there is no method for indoor localization in the healthcare context that delivers centimeter‐level precision. Although radio‐based localization has intriguing potential, the primary limitations of such a method are non‐line‐of‐sight radio signal transmission and multipath reflection, both of which lead to the lowest accuracy. The advanced 5G communication technology allows for the simultaneous utilization of temporal and angular features of a broadcast signal, as well as its multipath property, to accomplish precise target localization. This article presents a method for multipath channel‐assisted localization in the AAL system by utilizing the temporal and angular measurement of the signal concurrently. We simulated and tested the localization approach in an AAL system and achieved centimeter‐level accuracy over 90% of the time in all four cases.