Improving health outcomes for the elderly an analytic framework

The authors present an analytic framework for investigating interactive gaming technologies and integrating a number of such technologies into a remote healthcare monioring system (ReMoteCare) to help improve the quality of life of the elderly, the chronically unwell and infirm whether they are living in their own homes or in aged care facilities. The framework covers population characteristics of the cohort, the interactive technologies as well as economic and environmental factors. It is anticipated that a series of interactive exercises, developed in conjunction with a Feldenkrais movement therapist who specializes in exercises for the elderly, will help to improve the physical and mental health outcomes of this cohort

Smart and Pervasive Healthcare

Smart and pervasive healthcare aims at facilitating better healthcare access, provision, and delivery by overcoming spatial and temporal barriers. It represents a shift toward understanding what patients and clinicians really need when placed within a specific context, where traditional face-to-face encounters may not be possible or sufficient. As such, technological innovation is a necessary facilitating conduit. This book is a collection of chapters written by prominent researchers and academics worldwide that provide insights into the design and adoption of new platforms in smart and pervasive healthcare. With the COVID-19 pandemic necessitating changes to the traditional model of healthcare access and its delivery around the world, this book is a timely contribution

DevOps for Trustworthy Smart IoT Systems

ENACT is a research project funded by the European Commission under its H2020 program. The project consortium consists of twelve industry and research member organisations spread across the whole EU. The overall goal of the ENACT project was to provide a novel set of solutions to enable DevOps in the realm of trustworthy Smart IoT Systems. Smart IoT Systems (SIS) are complex systems involving not only sensors but also actuators with control loops distributed all across the IoT, Edge and Cloud infrastructure. Since smart IoT systems typically operate in a changing and often unpredictable environment, the ability of these systems to continuously evolve and adapt to their new environment is decisive to ensure and increase their trustworthiness, quality and user experience. DevOps has established itself as a software development life-cycle model that encourages developers to continuously bring new features to the system under operation without sacrificing quality. This book reports on the ENACT work to empower the development and operation as well as the continuous and agile evolution of SIS, which is necessary to adapt the system to changes in its environment, such as newly appearing trustworthiness threats

DevOps for Trustworthy Smart IoT Systems

ENACT is a research project funded by the European Commission under its H2020 program. The project consortium consists of twelve industry and research member organisations spread across the whole EU. The overall goal of the ENACT project was to provide a novel set of solutions to enable DevOps in the realm of trustworthy Smart IoT Systems. Smart IoT Systems (SIS) are complex systems involving not only sensors but also actuators with control loops distributed all across the IoT, Edge and Cloud infrastructure. Since smart IoT systems typically operate in a changing and often unpredictable environment, the ability of these systems to continuously evolve and adapt to their new environment is decisive to ensure and increase their trustworthiness, quality and user experience. DevOps has established itself as a software development life-cycle model that encourages developers to continuously bring new features to the system under operation without sacrificing quality. This book reports on the ENACT work to empower the development and operation as well as the continuous and agile evolution of SIS, which is necessary to adapt the system to changes in its environment, such as newly appearing trustworthiness threats

Contextual Anomaly Detection Framework for Big Sensor Data

Performing predictive modelling, such as anomaly detection, in Big Data is a difficult task. This problem is compounded as more and more sources of Big Data are generated from environmental sensors, logging applications, and the Internet of Things. Further, most current techniques for anomaly detection only consider the content of the data source, i.e. the data itself, without concern for the context of the data. As data becomes more complex it is increasingly important to bias anomaly detection techniques for the context, whether it is spatial, temporal, or semantic. The work proposed in this thesis outlines a contextual anomaly detection framework for use in Big sensor Data systems. The framework uses a well-defined content anomaly detection algorithm for real-time point anomaly detection. Additionally, we present a post-processing context-aware anomaly detection algorithm based on sensor profiles, which are groups of contextually similar sensors generated by a multivariate clustering algorithm. The contextual anomaly detection framework is evaluated with respect to two different Big sensor Data data sets; one for electrical sensors, and another for temperature sensors within a building

Usability analysis of contending electronic health record systems

In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study. © 2019 American Psychological Association Inc. All rights reserved.Peer reviewe

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse