Intelligent IoT-Driven Health Monitoring System for Real-Time Remote Patient Care and Early Disease Detection

The rise of chronic diseases and an aging population underscore the need for continuous and accessible healthcare monitoring, especially in remote areas. Traditional healthcare systems often face challenges such as lengthy diagnoses, inadequate treatment, and rising costs. To address these issues, this study presents an Internet of Things (IoT)-based real-time health monitoring system designed for proactive healthcare. We utilized various sensors to track essential health metrics—body temperature, heart rate, and oxygen saturation—transmitting the data to cloud platforms like Ubidots for analysis and visualization. Additionally, we developed a machine learning model to classify and predict heart disease using a separate dataset, enhancing diagnostic capabilities. The Blynk application facilitates remote access to this data, improving patient engagement and system accessibility. Furthermore, our system incorporates video surveillance through Ivideon to bolster telemedicine services, enabling immediate alerts for health abnormalities and allowing prompt interventions. This innovative approach significantly impacts the IoT and healthcare sectors, promoting early detection of health issues, encouraging proactive management, and reducing healthcare costs.