I-Health: Leveraging Edge Computing and Blockchain for Epidemic Management

Abdellatif, Alaa Awad; Samara, Lutfi; Mohamed, Amr; Erbad, Aiman; Chiasserini, Carla Fabiana; Guizani, Mohsen; O'Connor, Mark Dennis; Laughton, James

Epidemic situations typically demand intensive data collection and management from different locations/entities within a strict time constraint. Such demand can be fulfilled by leveraging the intensive and easy deployment of the Internet of Things (IoT) devices. The management and containment of such situations also rely on cross-organizational and national collaboration. Thus, this paper proposes an Intelligent-Health (I-Health) system that aims to aggregate diverse e-health entities in a unique national healthcare system by enabling swift, secure exchange and storage of medical data. In particular, we design an automated patients monitoring scheme, at the edge, which enables the prompt discovery, remote monitoring, and fast emergency response for critical medical events, such as emerging epidemics. Furthermore, we develop a blockchain optimization model that aims to optimize medical data sharing between different health entities to provide effective and secure health services. Finally, we show the effectiveness of our system, in adapting to different critical events, while highlighting the benefits of the proposed I-Health system.