Industry 4.0 was introduced in 2011 and since then has been perceived in multiple ways such as a vision, a paradigm, a scenario or as a digital revolution in production and service organizations. Even though Industry 4.0 is associated with great improvements for companies, there is still a lack of a uniform definition of the term Industry 4.0, especially when it comes to the transfer of knowledge from theoretical research to the implementation in organizations, which leads to confusion and disaffirmation. The lack of a clear structure and a holistic definition of the research topic Industry 4.0 inhibits the development of new business areas and new research approaches. To target this fundamental gap, a methodology is developed and the 338 most relevant publications are analyzed in the database of ScienceDirect starting from 2015. Based on those publications, the field of Industry 4.0 is structured. A consistent and comprehensive definition for Industry 4.0 is introduced by using a bibliometric analysis. Therefore, existing descriptions are decomposed into word fragments and analyzed. It is shown that this novel approach to find a definition for the term “Industry 4.0” does not yet exist. The aim is to provide a purely objective definition based on a statistical evaluation, without restricting the selection of publications to a specific research or business area. Based on those data, a new and ubiquitous definition of Industry 4.0 is formed, discussed and validated on practical examples.
There is a growing consensus in the global health community that the use of communication technologies will be an essential factor in ensuring universal health coverage of the world’s population. New technologies can only be used profitably if their accuracy is sufficient. Therefore, we explore the feasibility of using Apple’s ARKit technology to accurately measure the distance from the user’s eye to their smartphone screen. We developed an iOS application for measuring eyes-to-phone distances in various angles, using the built-in front-facing-camera and TrueDepth sensor. The actual position of the phone is precisely controlled and recorded, by fixing the head position and placing the phone in a robotic arm. Our results indicate that ARKit is capable of producing accurate measurements, with overall errors ranging between 0.88% and 9.07% from the actual distance, across various head positions. The accuracy of ARKit may be impacted by several factors such as head size, position, device model, and temperature. Our findings suggest that ARKit is a useful tool in the development of applications aimed at preventing eye damage caused by smartphone use.
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