The emergence of Industry 4.0 and the Internet of Things (IoT) has meant that the manufacturing industry has evolved from embedded systems to cyber-physical systems (CPSs). This transformation has provided manufacturers with the ability to measure the performance of industrial equipment by means of data gathered from on-board sensors. This allows the status of industrial systems to be monitored and can detect anomalies. However, the increased amount of measured data has prompted many companies to investigate innovative ways to manage these volumes of data. In recent years, cloud computing and big data technologies have emerged among the scientific communities as key enabling technologies to address the current needs of CPSs. This paper presents a large-scale platform for CPS real-time monitoring based on big data technologies, which aims to perform real-time analysis that targets the monitoring of industrial machines in a real work environment. This paper is validated by implementing the proposed solution on a real industrial use case that includes several industrial press machines. The formal experiments in a real scenario are conducted to demonstrate the effectiveness of this solution and also its adequacy and scalability for future demand requirements. As a result of the implantation of this solution, the overall equipment effectiveness has been improved.INDEX TERMS Anomaly detection, big data, cyber-physical system, industry 4.0, real-time processing.
Ambient Assisted Living environments provide support to people with disabilities and elderly people, usually at home. This concept can be extended to public spaces, where ubiquitous accessible services allow people with disabilities to access intelligent machines such as information kiosks. One of the key issues in achieving full accessibility is the instantaneous generation of an adapted accessible interface suited to the specific user that requests the service. In this paper we present the method used by the EGOKI interface generator to select the most suitable interaction resources and modalities for each user in the automatic creation of the interface. The validation of the interfaces generated for four different types of users is presented and discussed.
Accessibility User interface development method Model driven development User Interface Description LanguageIt is a legal requirement in many countries to ensure accessibility for Web applications. Although there are numerous regulations and standards regarding accessibility in the de-velopment of user interfaces, accessibility is nevertheless quite difficult to achieve, let alone to maintain at a high level of quality throughout the development process. This difficulty is due to diverse factors including, but not limited to, the lack of proper development meth-ods, authoring tools and accessibility training for user interface development professionals. In an attempt to offer a solution to these difficulties, this paper proposes a methodological approach for the integration of accessibility requirements into a user interface develop-ment method based on User Interface Description Language (UIDL) or, more specifically, on the USer Interface eXtensible Markup Language (UsiXML) framework. The proposed strat-egy involves the integration of accessibility requirements into design primitives of the user interface development method. This paper focuses on accessibility requirements related to navigation in the Task Model, Abstract User Interface Model and Transformation Model. The application of the approach shown for the SPA4USXML tool also includes a proof of concept and validation of the proposal. The study shows that accessibility requirements included at the design stage in the modelling of user interfaces can be systematized through mech-anisms such as new transformation rules and the use of support tools such as SPA4USXML.
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