Abstract: A system and method for providing compliance predictions for using a respiratory pressure therapy device in a treatment regimen is disclosed. The system includes a respiratory pressure therapy device having a transmitter and an air control device to provide respiratory therapy to a patient. The respiratory pressure therapy device collects operational data and transmits the collected operational data. Demographic data of the patient is collected. A predicted compliance with the treatment regimen is determined based on inputting operational data and demographic data to a machine learning compliance prediction model having a compliance prediction output. The machine learning model is trained from the operational data and demographic data of a population of patients using respiratory pressure therapy devices.

Abstract: The disclosure relates to sensor network, machine type communication (MTC), machine-to-machine (M2M) communication, and technology for internet of things (IoT). The disclosure may be applied to intelligent services based on the above technologies, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. The disclosure describes a method and system for routine disruption handling and routine management in a smart environment. A method for operating an apparatus is provided.

Abstract: The disclosure relates to sensor network, machine type communication (MTC), machine-to-machine (M2M) communication, and technology for internet of things (IoT). The disclosure may be applied to intelligent services based on the above technologies, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. The disclosure describes a method and system for routine disruption handling and routine management in a smart environment. A method for operating an apparatus is provided.