Improving Healthcare Efficiency via Sensor-Based Remote Monitoring of Patient Health Utilizing an Enhanced AdaBoost Algorithm

This paper presents a novel approach to remote patient monitoring using the integration of Internet of Things (IoT) and Artificial Intelligence (AI) technologies. The proposed system is designed to automatically detect and monitor the health status of patients from a remote location. The proposed solution uses a combination of connected devices, cloud-based data storage, and machine learning algorithms to monitor and track patients’ health remotely. It incorporates IoT sensors to collect real-time health data, such as body temperature, heart rate, glucose meter, and blood pressure and uses AI algorithms to analyse and interpret this data. The system can provide early warning signs of health issues, alert healthcare providers in real time, and facilitate timely interventions. The proposed solution has the potential to improve patient outcomes, reduce healthcare costs, and increase access to healthcare services. This paper discusses the technical details of the proposed system and its potential impact on the healthcare industry. This paper also highlights future directions for research and development in this area.