With the rising prevalence of chronic diseases, continuous health monitoring is crucial to enhance patient outcomes. This study explores an IoT-enabled health monitoring and advisory system designed to track important signs likes heart rate, blood pressure, and temperature etc. The system aims to improve healthcare accessibility by reducing the need for frequently visiting the hospital, that is  in-person visits and allowing remote monitoring. The proposed system uses wearable sensors, a mobile application, and cloud infrastructure to capture and transmit health metrics continuously. Data is stored and processed on a cloud server, where an intelligent advisory module analyzes it to generate personalized recommendations and alerts, accessible by patients and healthcare providers. System evaluation shows high accuracy in real-time data collection and health status monitoring. The advisory module effectively provides actionable insights, supporting early detection of health anomalies and promoting proactive healthcare management. This IoT-based health monitoring system demonstrates potential for transforming healthcare delivery by enabling continuous tracking and timely interventions. It offers a scalable solution for healthcare accessibility, particularly in underserved areas. Future enhancements include machine learning integration to improve predictive accuracy. The methodology used in the system is the Object Oriented methodology. The Object Oriented methodology develops and refines the app based on user feedback and changing requirements. It breaks down the development process into small, manageable tasks or sprints, each focused on delivering specific features or enhancements.

Keywords
IoT, health monitoring, real-time tracking, remote healthcare, personalized recommendations, preventive care