Quality of Service Framework on IoT-Fog Computing for Smart Healthcare Services
The recent advancement of technology is moving from a smart system to a smart city. The smart city concept includes various smart components such as smart hospitals, smart homes, smart energy systems, smart colleges/universities, smart buildings, etc. which have a major impact on city life. The healthcare sector is always growing while technologies are updating and emerging. Internet of Things (IoT), big data, artificial intelligence (AI), machine learning, cloud computing, fog computing, and edge computing provide their best effort for successful implementation of the smart healthcare system in a smart city. Fog computing is in excellent shape for delay-sensitive real-time applications of the health care sector whereas AI provides an efficient way to predict the health diseases at an early stage. In this chapter, the quality of service framework using IoT-Fog computing for smart healthcare for smart cities is proposed. It utilizes the concept of AI integrating with Fog computing. The proposed framework provides real-time processing of users’ health data to diagnose the possibility of chronic illness at an early stage. A case study of swine flu (H1F1 flu) is used to demonstrate the working of the proposed framework. iFogSim and python language are used to simulate the scenario as well as evaluate the proposed framework. The proposed framework is validated by comparing with IoT-cloud traditional framework in terms of QoS parameters, i.e. overall response time, classification accuracy, recall, and f-measure.