Indoor Geolocation Demonstrator: Enhancing Efficiency Through Real-Time Tracking and AI Optimization

The integration of indoor geolocation technologies within hospital environments presents a significant opportunity to understand circulation patterns, identify congestion areas, and optimize care processes. In this paper, we propose a complete framework of indoor geolocation solutions tailored to hospital settings, aiming to understand circulation patterns, identify congestion areas, and optimize care processes. The framework includes the development and deployment of ESP32-based devices to capture MAC addresses via BLE and WiFi sniffing, and the use of AI models to predict the tracking speed of these addresses. Our results demonstrate improved patient flow management and enhanced care coordination through real-time tracking and data analysis.