Alaa Awad Abdellatif

TL;DR: The vision of exploiting MEC for s-health applications is envisioned and two main functionalities that can be implemented leveraging such an architecture to provide efficient data delivery are presented, namely, multimodal data compression and edge-based feature extraction for event detection.

TL;DR: This article designs an automated patients monitoring scheme, at the edge, which enables the remote monitoring and efficient discovery of critical medical events, and develops a blockchain-based optimization model that aims to optimize the latency and computational cost of medical data exchange between different health entities, hence providing effective and secure healthcare services.

TL;DR: A novel smart and secure Healthcare system (ssHealth), which, leveraging advances in edge computing and blockchain technologies, permits epidemics discovering, remote monitoring, and fast emergency response and allows for secure medical data exchange among local healthcare entities.

TL;DR: A reliable energy-efficient emergency notification system for epileptic seizure detection, based on conceptual learning and fuzzy classification, and a selective data transfer scheme, which opts for the most convenient way for data transmission depending on the detected patient’s conditions.

TL;DR: The goal is to adaptively reduce the amount of data that needs to be transmitted in order to efficiently communicate and possibly store information, while maintaining the required application quality-of-service (QoS) requirements.