Health monitoring is the continuous tracking and observation of a patient’s health-related parameters, such as vital signs, activity levels, and medical conditions. This can be done through various technologies and devices to provide real-time data for assessing and managing a person’s well-being. In this paper, the primary objective is to enhance the health monitoring system through presenting the Private Remote Interface (PRI). We collected the health records of 4287 patients using different brands of smartwatches and applied deep learning algorithms to create a system that controls the patient’s health records. Moreover, our approach is centered on the development of a smart control system for patient health monitoring, leveraging the power of deep learning algorithms. The utilization of deep learning allows for a comprehensive analysis of health data. Similarly, we defined three important rules for collecting the patients’ records: The most important rule is keeping the patient information private. Second is the satisfaction of patients, focusing on delivering a system that follows their needs and preferences. Lastly, privacy concerns are addressed due to the sensitivity of health data, emphasizing the ethical handling and protection of patient information.