IoT Based Effective Wearable Healthcare Monitoring System For Remote Areas

The research introduces an IoT-based personal healthcare monitoring system for rural areas with poor healthcare. Data processing, machine learning, and deep learning monitor vital signs with 96.5% accuracy, better than current approaches. The complete technique employs many data points to demonstrate rural residents’ social and health features. This ensures the system works in challenging scenarios. With 0.94 precision, health data recognition was accurate. This degree of information is crucial for making wise medical decisions, particularly in low-resource areas where traveling to a hospital is difficult. The system uses 2.5 W every hour, making it energy efficient. This allows it to operate reliably even when the power goes off. Comparing the recommended approach against established methods with various models consistently indicates its superiority. IoT-based personal healthcare tracking is more accurate, precise, and energy-efficient than existing approaches. These data demonstrate the system’s power to transform remote healthcare. They demonstrate their ability to monitor key health variables and maintain stability, durability, and energy efficiency. The authors discuss the study’s limitations and wider implications at the conclusion. Before the approach may be extensively employed, connection and device cost issues must be addressed. The research highlights how technology has enhanced healthcare monitoring and emphasizes the need for community-specific solutions for rural and underprivileged individuals. The recommended IoT-based smart healthcare monitoring system advances technology and makes healthcare access more equal and accessible to disadvantaged groups.