Innovative Business Model for Smart Healthcare Insurance

Information revolution and technology growth have made a considerable contribution to restraining the cost expansion and empowering the customer. They disrupted most business models in different industries. The customer-centric business model has pervaded the different sectors. Smart healthcare has made an enormous shift in patient life and raised their expectations of healthcare services quality. Healthcare insurance is an essential business in the healthcare sector; patients expect a new business model to meet their needs and enhance their wellness. This research develops a holistic smart healthcare architecture based on the recent development of information and communications technology. Then develops a disruptive healthcare insurance business model that adapts to this architecture and classifies the patient according to their technology needs. Finally, and implementing a prototype of a system that matches and suits the healthcare recipient condition to the proper healthcare insurance policy by applying Web Ontology Language (OWL) and rule-based reasoning model using SWRL using Protég

Industry 4.0 Technology: A Cross-Industry View of Adoption, Usage and COVID-19 Effects

Industry 4.0 technology (I4.0) is inescapable. It transforms the way businesses and customers interact and revolutionizes how organizations produce goods and services (SAP Insights, 2020). It requires a level of agility that many organizations do not possess. Defending against disruptive business models is no longer enough. Organizations must be nimble to optimize assets and resources in response to adversity. In March 2020, the coronavirus (COVID-19) pandemic ushered a devastating blow to the U.S. economy and job market with pervasive shocks that continue to be a business threat. In response, many organizations are accelerating automation, digitization, and communication capabilities to close the gap and connect with customers. This dissertation examined the cross-industry adoption of the nine most common Industry 4.0 technologies: big data, artificial intelligence, cloud computing, the internet of things, cybersecurity, 3-D printing, autonomous technology, augmented reality, and blockchain. This descriptive study explored factors of I4.0 adoption across industries and organizational sizes during a national pandemic. The study sought to reveal “what” factors contributed to the adoption of Industry 4.0, “what” industry patterns exist, “what” effect COVID-19 had on these concepts. A quantitative method was used to examine the relationship between factors. An online survey was administered to a Qualtrics panel of 520 business owners and executives to capture perceptions, knowledge, and insights. A binary logistic regression analysis was performed. The results of this study inform a cross-industry framework of I4.0 technology adoption, which includes contributing factors. The findings also showed COVID-19 was less an accelerant of adoption but rather, the industry sector was a greater influencer

An overview of IoT architectures, technologies, and existing open-source projects

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract]: Today’s needs for monitoring and control of different devices in organizations require an Internet of Things (IoT) platform that can integrate heterogeneous elements provided by multiple vendors and using different protocols, data formats and communication technologies. This article provides a comprehensive review of all the architectures, technologies, protocols and data formats most commonly used by existing IoT platforms. On this basis, a comparative analysis of the most widely used open source IoT platforms is presented. This exhaustive comparison is based on multiple characteristics that will be essential to select the platform that best suits the needs of each organization.This research/work has been supported by GAIN (Galician Innovation Agency) and the Regional Ministry of Economy, Employment and Industry, Xunta de Galicia under grant COV20/00604 through the ERDF Galicia 2014-2020; and by grant PID2019-104958RB-C42 (ADELE) funded by MCIN/AEI/10.13039/501100011033 . Funding for open access charge: Universidade da Coruña/CISUG.Xunta de Galicia; COV20/0060

Concevoir des applications internet des objets sémantiques

According to Cisco's predictions, there will be more than 50 billions of devices connected to the Internet by 2020.The devices and produced data are mainly exploited to build domain-specific Internet of Things (IoT) applications. From a data-centric perspective, these applications are not interoperable with each other.To assist users or even machines in building promising inter-domain IoT applications, main challenges are to exploit, reuse, interpret and combine sensor data.To overcome interoperability issues, we designed the Machine-to-Machine Measurement (M3) framework consisting in:(1) generating templates to easily build Semantic Web of Things applications, (2) semantically annotating IoT data to infer high-level knowledge by reusing as much as possible the domain knowledge expertise, and (3) a semantic-based security application to assist users in designing secure IoT applications.Regarding the reasoning part, stemming from the 'Linked Open Data', we propose an innovative idea called the 'Linked Open Rules' to easily share and reuse rules to infer high-level abstractions from sensor data.The M3 framework has been suggested to standardizations and working groups such as ETSI M2M, oneM2M, W3C SSN ontology and W3C Web of Things. Proof-of-concepts of the flexible M3 framework have been developed on the cloud (http://www.sensormeasurement.appspot.com/) and embedded on Android-based constrained devices.Selon les prévisions de Cisco , il y aura plus de 50 milliards d'appareils connectés à Internet d'ici 2020. Les appareils et les données produites sont principalement exploitées pour construire des applications « Internet des Objets (IdO) ». D'un point de vue des données, ces applications ne sont pas interopérables les unes avec les autres. Pour aider les utilisateurs ou même les machines à construire des applications 'Internet des Objets' inter-domaines innovantes, les principaux défis sont l'exploitation, la réutilisation, l'interprétation et la combinaison de ces données produites par les capteurs. Pour surmonter les problèmes d'interopérabilité, nous avons conçu le système Machine-to-Machine Measurement (M3) consistant à: (1) enrichir les données de capteurs avec les technologies du web sémantique pour décrire explicitement leur sens selon le contexte, (2) interpréter les données des capteurs pour en déduire des connaissances supplémentaires en réutilisant autant que possible la connaissance du domaine définie par des experts, et (3) une base de connaissances de sécurité pour assurer la sécurité dès la conception lors de la construction des applications IdO. Concernant la partie raisonnement, inspiré par le « Web de données », nous proposons une idée novatrice appelée le « Web des règles » afin de partager et réutiliser facilement les règles pour interpréter et raisonner sur les données de capteurs. Le système M3 a été suggéré à des normalisations et groupes de travail tels que l'ETSI M2M, oneM2M, W3C SSN et W3C Web of Things. Une preuve de concept de M3 a été implémentée et est disponible sur le web (http://www.sensormeasurement.appspot.com/) mais aussi embarqu

The Application of Design Thinking on Evaluating a User Self-Service Data Analytics/Science Platform

This thesis is aimed at utilising design thinking and the first half of the double diamond framework to i) set-up a research and select the appropriate participants, ii) gather requirements and define user personas from those eligible participants, and then iii) define the framework for evaluating a user self-service data analytics/science platform. Derived from the author’s own experiences, both as a Business Analyst (BA) and Citizen Data Scientist, with no-, low-, and code-based data analytics and science platforms are being implemented for enabling user self-service analytics – for users who are completely new to the space of data analysis and science as well as those who are experienced analysts and data scientists across a variety of industries and global regions – and there has been a need to outline an enablement process for this space. Through this research, the current state of the marketplace is researched, analysed, and evaluated alongside user research carried out on the feasibility and applicability of a UI- and UX-centric framework for ensuring human-centred design. A literature review showcases the benefits of human-centred design for humans when it comes to usability and techniques for such an application in various other fields. The key aspects of this research are to understand the users’ capabilities, needs, and wants, then categorise those users into personas, analyse and segment the requirements, create functional and non-functional requirements for platform capabilities, and then, ultimately, provide an evaluation framework for any organisation and/or individual looking for a user self-service data analytics/science platform by carrying out a pilot research study on ten (10) participants

Engineering Blockchain Based Software Systems: Foundations, Survey, and Future Directions

Many scientific and practical areas have shown increasing interest in reaping the benefits of blockchain technology to empower software systems. However, the unique characteristics and requirements associated with Blockchain Based Software (BBS) systems raise new challenges across the development lifecycle that entail an extensive improvement of conventional software engineering. This article presents a systematic literature review of the state-of-the-art in BBS engineering research from a software engineering perspective. We characterize BBS engineering from the theoretical foundations, processes, models, and roles and discuss a rich repertoire of key development activities, principles, challenges, and techniques. The focus and depth of this survey not only gives software engineering practitioners and researchers a consolidated body of knowledge about current BBS development but also underpins a starting point for further research in this field