IOT AND AI BASED HEART RATE MONITORING SYSTEM

In this work, an IoT and AI-based heart rate monitoring system has been designed and implemented for continuous, real-time patient monitoring. The system integrates wearable sensors to collect heart rate data, IoT modules for wireless transmission, and cloud-based platforms for data storage and processing. AI algorithms were employed to detect abnormal heart rate patterns, enabling early detection of cardiac anomalies such as tachycardia and bradycardia.   Experimental results demonstrate that the proposed system achieves high accuracy (>95%) in detecting abnormal conditions, low latency in data transmission, and reliable real-time performance. The automated alert system allows healthcare providers and patients to respond promptly, reducing risks associated with delayed intervention.    Compared to conventional monitoring systems, the integration of IoT and AI provides scalability, remote accessibility, and predictive healthcare capabilities, making it suitable for both clinical and home environments. In conclusion, the proposed system lays a foundation for intelligent, real-time cardiac monitoring and has strong potential to advance preventive healthcare, reduce hospital visits, and enhance patient quality of life. Future enhancements can further transform it into a comprehensive remote health monitoring solution.  

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