ADAPTIVE AI-POWERED VOMITING PREVENTION AND MOTION SICKNESS MANAGEMENT

The present invention relates to an adaptive artificial intelligence-powered vomiting prevention and motion sickness management system designed for predicting, preventing, and managing motion sickness in passengers across moving vehicles and virtual environments comprising a wearable device integrated with a biosensor suite, vehicle motion sensors, and environmental sensors, operatively coupled to a data acquisition hub and a sensor fusion module for generating a unified dataset. A machine learning–based symptom inference model predicts motion sickness risk prior to onset, while a control policy engine dynamically selects personalized preventive interventions including visual stabilization, haptic feedback, guided breathing, aromatherapy, airflow and lighting control, seat orientation adjustment, and vibration damping. An adaptive learning module continuously updates passenger-specific profiles using real-time and historical data, enabling refinement of prediction accuracy and intervention effectiveness. The system supports multi-passenger deployment, distributed edge–cloud processing, clinician access, and emergency overrides, with provisions for OTA updates and data privacy safeguards. The invention further discloses a method for predicting and preventing motion sickness by integrating real-time physiological, motion, and environmental data with AI-driven prediction and personalized interventions, thereby proactively mitigating nausea and vomiting and enhancing passenger comfort and operational efficiency in diverse transport and immersive environments.