The rapid growth of healthcare technologies and the increasing demand for continuous patient care have led to the development of AI-driven smart healthcare monitoring systems. These systems integrate artificial intelligence (AI), Internet of Things (IoT) devices, wearable sensors, and cloud computing to monitor patients' health conditions in real time. By collecting physiological data such as heart rate, blood pressure, body temperature, oxygen saturation, and activity levels, the system can analyze health patterns and detect abnormalities at an early stage. Machine learning algorithms enable accurate prediction of potential health risks, allowing healthcare providers to take preventive measures and improve patient outcomes. Furthermore, remote monitoring capabilities reduce hospital visits, lower healthcare costs, and enhance access to medical services, especially for elderly and chronically ill patients. The proposed AI-driven smart healthcare monitoring system offers a reliable, efficient, and scalable solution for personalized healthcare management by providing real-time alerts, data analytics, and decision support for both patients and medical professionals.