Abstract
The Internet of Things (IoT) facilitates creation of smart spaces by converting existing environments into sensor-rich data-centric cyber-physical systems with an increasing degree of automation, giving rise to Industry 4.0. When adopted in commercial/industrial contexts, this trend is revolutionising many aspects of our everyday life, including the way people access and receive healthcare services. As we move towards Healthcare Industry 4.0, the underlying IoT systems of Smart Healthcare spaces are growing in size and complexity, making it important to ensure that extreme amounts of collected data are properly processed to provide valuable insights and decisions according to requirements in place. This paper focuses on the Smart Healthcare domain and addresses the issue of data fusion in the context of IoT networks, consisting of edge devices, network and communications units, and Cloud platforms. We propose a distributed hierarchical data fusion architecture, in which different data sources are combined at each level of the IoT taxonomy to produce timely and accurate results. This way, mission-critical decisions, as demonstrated by the presented Smart Healthcare scenario, are taken with minimum time delay, as soon as necessary information is generated and collected. The proposed approach was implemented using the Complex Event Processing technology, which natively supports the hierarchical processing model and specifically focuses on handling streaming data ‘on the fly’—a key requirement for storage-limited IoT devices and time-critical application domains. Initial experiments demonstrate that the proposed approach enables fine-grained decision taking at different data fusion levels and, as a result, improves the overall performance and reaction time of public healthcare services, thus promoting the adoption of the IoT technologies in Healthcare Industry 4.0.
Highlights
Healthcare is one of the many domains, continuously improved by the pervasive penetration of Internet of Things (IoT) technologies, which are used to support core functions of healthcare institutions
The emerging Healthcare Industry 4.0 relies on the ubiquitous presence of smart sensing devices to enable timely data collection and decision
To address the time constraints and deal with the increasing number of heterogeneous data sources, this paper proposed a distributed hierarchical data fusion approach, utilising the processing capabilities of individual nodes of the Smart Healthcare ecosystem, splitting data fusion tasks between smart edge objects (i.e. Edge computing), communication and processing units (i.e. Fog computing), and remote datacenters (i.e. Cloud computing)
Summary
Healthcare is one of the many domains, continuously improved by the pervasive penetration of IoT technologies, which are used to support core functions of healthcare institutions. Numerous devices, equipped with a wide range of sensing resources, as well as relatively advanced computing, storage and communication capabilities ( earning the smart attribute), are ubiquitously present in people’s life aiming to improve it Such sensor-enabled smart objects are Internet-connected, thereby creating a global network of remotely accessible data sources, ready to be discovered and integrated into complex cyber-physical systems. It is important to ensure that Health 4.0 is realised not via vertical non-sustainable solutions aiming to ‘smarten’ individual, isolated clinics and hospitals, but rather via an all-encompassing Smart Healthcare solution, able to cover much wider scenarios, involving multiple organisations and stakeholders From this perspective, further implementation of the (Smart) Healthcare Industry 4.0 vision requires a global approach and depends on a technological convergence among various ICT domains, including IoT, Big Data analytics, and Cloud Computing
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