Wearable Sensors and IoT Integration for Predictive Healthcare: Challenges and Opportunities
Keywords:
IoT in healthcare, Wearable sensors, Predictive analytics, Digital health, Machine learning, Preventive medicine, Remote monitoring, Smart healthcare systems.Abstract
The rapid evolution of the Internet of Things (IoT) and wearable sensor technologies has opened new frontiers in digital healthcare. Predictive healthcare, powered by data analytics and machine learning, enables early diagnosis, real-time monitoring, and preventive interventions before symptoms become critical. This research explores the role of wearable sensors integrated with IoT platforms in predictive healthcare management. The study evaluates the accuracy, efficiency, and challenges of IoT-enabled devices in chronic
disease monitoring, lifestyle management, and emergency detection. Data were collected from 180 participants using smart wearables over 10 months, followed by data analysis and physician feedback. The findings reveal that IoT-based predictive healthcare reduced emergency incidents by 42%, improved patient engagement by 37%, and enhanced diagnostic accuracy through real-time alerts.
The paper concludes by discussing future opportunities and policy recommendations for scaling IoT integration in healthcare ecosystems.
