Enhancing the Processing of Healthcare Data Streams using Fog Computing Healthcare data streams originate from various sensors and Internet of Things (IoT) devices deployed in medical equipment and healthcare facilities as well as worn by patients. These vast volumes of data need to be leveraged to improve patient care, optimize processes, and help health sector stakeholders and applications make faster and more informed decisions. Many healthcare applications use the power of the cloud for data processing. However, timesensitive healthcare applications cannot tolerate sending data streams to the cloud for processing due to unacceptable high latency and network bandwidth requirements. Healthcare facilities and caregivers need the ability to efficiently stream data and process data streams in realtime at the edge. This paper describes a fivetier architecture that aims to deal with the streaming and processing of data generated by the various devices and equipment of healthcare facilities and systems to enable the creation of smart healthcare applications. The architecture is based on emerging and established technologies, including IoT, edgefog computing, data integration techniques, cloud computing, and data analytics. The proposed architecture will facilitate the creation of healthcare applications for realtime event detection, notification of alerts, and building monitoring dashboards. Fog node components include an advanced and widely recognized distributed messaging system, Apache Kafka, and the popular stream processing engine, Apache Storm, capable of processing large amounts of data.

Health Fog for Smart Healthcare Internet of Things (IoT) and sensing have led to significant improvements in the delivery of healthcare. IoT can extend its scope by accessing cloud resources. Cloud, on the other hand, can also enhance its services from the data collected from healthcare IoTs. However, IoT and the cloud are generally physically distant from each other making it a challenge to provide services with specific requirements (such as fast response time, less computeintensive processing). To address these requirements, we need some type of middleware technology such as a fog which resides between the cloud and IoT ecosystem. We describe how fog enables cloudIoT convergence and can be deployed to achieve smart healthcare. We present a few use cases where the use of fog can improve healthcare delivery. Finally, we discuss relevant issues and opportunities that must be considered in the future in order to realize the smart healthcare vision.