Patient Monitoring System Used Smart Sensor Technology Internet of Things and AI

Abstract

In recent years, advancements on the Internet of Things (IoT) and Artificial Intelligence (AI) have significantly transformed the healthcare sector, particularly in patient monitoring and management. This research presents the development of a smart patient monitoring system that utilizes IoT-based sensor technology integrated with AI for real-time health data acquisition, processing, and analysis. The system is designed to continuously monitor vital signs such as body temperature, heart rate, blood pressure levels either Systolic and Diastolic, and patient movement using a network of wearable and non-invasive smart sensors. These sensors transmit data wirelessly to a centralized cloud platform, where it is stored, visualized, and analyzed using AI-driven algorithms. The AI components are implemented to detect abnormal patterns and generate alerts for healthcare providers or caregivers in case of emergency or irregularities in a patient’s condition. The system is particularly useful for remote patient monitoring, chronic disease management, elderly care, and post-surgical recovery, reducing the need for constant physical supervision and hospital visits. It also supports early diagnosis and timely medical intervention, potentially improving treatment outcomes and reducing healthcare costs. The proposed system was tested in a simulated environment and demonstrated high accuracy in data collection, anomaly detection, and timely notifications. The results indicate that integrating IoT and AI technologies can enhance patient safety, increase monitoring efficiency, and support better healthcare decision-making. This study highlights the potential of smart sensor-based IoT and AI systems as scalable, reliable solutions for modern, connected healthcare services.