ADVANCING IOT BASED HEALTHCARE SYSTEMS USING EDGE INTELLIGENCE

This study presents an intelligent healthcare monitoring framework that integrates Internet of Things(IoT) technology with edge-based artificial intelligence for real-time cardiac analysis. Conventional cloud-centric systems often suffer from latency, bandwidth limitations, and privacy concerns, which restrict their effectiveness in time-critical medical applications. To address these challenges, the proposed architecture distributes computational intelligence across edge devices and edge servers, enabling rapid data processing and localized decision-making. Physiological signals acquired from wearable sensors are initially processed at the device level using lightweight algorithms for noise reduction and feature extraction. The proposed approach enhances response time, reduces communication overhead, and ensures data privacy while maintaining high diagnostic accuracy. Experimental observations demonstrate the effectiveness of the framework in supporting continuous and reliable cardiac monitoring. This work highlights the potential of edge intelligence in developing scalable and efficient next-generation healthcare systems.