Integrated Healthcare System for Vulnerable Populations: Leveraging IOT, Machine-Learning and Community Based Interventions

Healthcare systems face significant challenges in addressing the needs of vulnerable populations, including post-surgery patients and individuals with noncommunicable diseases such as diabetes and hypertension. While various studies have explored technology-driven healthcare solutions, the integration of multiple advanced technologies into a unified system tailored for these groups remains underdeveloped. This study proposes a comprehensive healthcare system that leverages adaptive learning, blockchain technology, predictive analytics, and IoT integration. Adaptive learning systems provide personalized health education and lifestyle recommendations, blockchain ensures secure health data management, predictive analytics enables early disease diagnosis and AI-driven drug adherence, and IoT devices facilitate continuous health monitoring. The research is supported by data collected from healthcare institutions and national statistical sources, following strict ethical guidelines. The proposed system has significant implications for improving healthcare accessibility, efficiency, and security. By offering a scalable model for personalized treatment strategies, early intervention, and enhanced patient outcomes, this study contributes to the advancement of integrated digital healthcare solutions.