AN ENERGY-EFFICIENT, LOW-LATENCY, AND SECURE COMMUNICATION FRAMEWORK FOR SMART HEALTHCARE IOT SYSTEMS
Keywords:
Smart Healthcare, IoT, Energy Optimization, Low Latency, Secure IoT Communication, Edge Computing, Fog Computing, Machine Learning, Predictive Monitoring.Abstract
The healthcare sector’s digital transformation, driven by the Internet of Things (IoT), has enabled continuous patient tracking, real time data analytics, and advanced clinical decisions through interconnected smart devices and sensors. Yet, these systems often suffer from excessive energy use, data-transmission delays, and serious security vulnerabilities. This study introduces an integrated communication framework designed to enhance energy efficiency, minimize latency, and strengthen data protection in smart healthcare IoT environments. The framework accomplishes quicker decision cycles and less reliance on the cloud by utilizing edge-fog computing for distributed processing and lightweight encryption for secure data management. For proactive healthcare responses, a multi-layer architecture that includes phases for acquisition, storage, analytics, and dissemination is enhanced using machine learning-based prediction models. The suggested method improves system responsiveness and prolongs device lifetime while preserving strong information confidentiality, according to experimental evaluation. It is therefore a feasible design for real-time, scalable healthcare ecosystems
