Routine Based Algorithm

Routine-based algorithms analyze repetitive patterns in data to identify and characterize habitual behaviors. Current research focuses on leveraging diverse data sources, such as wearable sensor data and vehicle telematics, employing techniques like Hawkes processes and anomaly detection to extract meaningful routine profiles. These algorithms find applications in diverse fields, including personalized healthcare, improving the efficiency of AI-assisted medical diagnosis, and enhancing security systems through behavioral biometrics. The resulting insights offer potential for improved user experience, enhanced diagnostic accuracy, and more effective security measures.