Real-Time In-Cabin Vital Sensing and Emergency Response Using Ultra-Wideband Radar in Automotive Environments

This study introduces a novel in-cabin health monitoring system leveraging Ultra-Wideband (UWB) radar technology for real-time, contactless detection of occupants' vital signs within automotive environments. By capturing micro-movements associated with cardiac and respiratory activities, the system enables continuous monitoring without physical contact, addressing the need for unobtrusive vehicle health assessment.​ The system architecture integrates edge computing capabilities within the vehicle's head unit, facilitating immediate data processing and reducing latency. Processed data is securely transmitted via HTTPS to a cloud-based backend through an API Gateway, which orchestrates data validation and routing to a machine learning pipeline. This pipeline employs supervised classifiers—Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Random Forest (RF)—to analyze features such as temporal heartbeat variability, respiration rate stability, and energy distribution patterns derived from radar-generated range-azimuth heatmaps.​ Empirical evaluations demonstrate the system's proficiency in classifying occupant states, including normal, distressed, and unconscious conditions, achieving high prediction accuracy with low false positive rates. Notably, the system attains sub-10-second detection latency and facilitates end-to-end emergency response actions within a 5-minute window.​ Integrating Advanced Driver-Assistance Systems (ADAS) and Emergency Response Systems (ERS) enhances vehicular safety protocols, enabling automated emergency maneuvers and real-time transmission of biometric data to medical responders. Furthermore, the cloud infrastructure supports the accumulation of health data, contributing to personalized driver profiles and informed decision-making for future interventions.​ This research underscores the potential of UWB radar technology in augmenting automotive safety through real-time health monitoring and responsive emergency systems, paving the way for smarter and more secure vehicular environments.