Dual-Channel Neural Intelligence for Healthcare Localization in Assisted Living Environments

Abstract

Healthcare localization has become a critical component of modern assisted living environments, enabling continuous monitoring, emergency response, patient tracking, and intelligent healthcare service delivery. With the growing elderly population and increasing demand for independent living solutions, accurate indoor localization technologies are essential for ensuring patient safety, improving quality of care, and supporting healthcare professionals in real-time decision-making. Conventional localization systems based on Wi-Fi, Bluetooth, RFID, and sensor networks often suffer from signal fluctuations, environmental interference, multipath effects, and reduced positioning accuracy. Recent advances in artificial intelligence have demonstrated significant potential for enhancing healthcare localization through intelligent feature learning and adaptive decision-making mechanisms. This research proposes a Dual-Channel Neural Intelligence Framework for Healthcare Localization in Assisted Living Environments (DCNI-HL) that integrates dual-channel sensor analytics, neural representation learning, and intelligent localization strategies for accurate patient positioning and activity monitoring.