Intelligent Sensor Data Fusion for Supporting Advanced Smart Health Processes

Abstract

Smart cities applications are now very relevant in both the academic and industrial settings. Smart health processes are among the most significant cases of smart cities applications, where the goal is to determine effective and efficient decision-making processes in the context of healthcare management. One way to achieve this goal is just introducing novel sensor data fusion algorithms and techniques, as to take advantages from the mature area of sensor data management and processing. This article proposes a system based on sensors data to identify the most appropriate solution to be activated when a health problem arises. In particular, the proposed system allows identifying anomalies, their assessment and their management.