This paper presents an entirely new approach to the use of virtual reality (VR) in the educational process for the needs of Industry 4.0. It is based on the proposed comprehensive methodology, including the design, creation, implementation and evaluation of individual courses implemented in a VR environment. An essential feature of the new methodology is its universality and comprehensiveness. Thanks to that, it can be applied in such areas as higher education, aviation, automotive, shipbuilding, energy and many others. The paper also identifies the significant advantages and disadvantages of VR-based education that may determine its use scope and profile. In addition, on the basis of the proposed methodology, a model of a training station using VR technology has been developed to enable the realization of training classes in the field of firefighting activities that should be undertaken during the hazard arising from the operation of a numerically controlled production machine. Results of the conducted training using this station were also presented. The study showed the potential of training based on a virtual environment to improve participants’ skills and knowledge. The development and implementation of adequate courses in the VR environment can reduce costs and increase the safety and efficiency of employees’ performed activities.

This paper presents the process for creating an integrated design and manufacturing environment supporting 3D printing as part of the structure of Industry 4.0. This process is based on a developed framework for the design of modern automated and computerized infrastructure. The task of the described system is to combine all the steps included in the operating range of incremental systems based on an IT platform by integrating data from individual areas, such as IT systems supporting remote 3D printing. The proposed framework for incremental processes is a universal solution that can be defined in detail by a single organizational unit running 3D printing, as well as by a cluster of entities related to 3D printing. In the initial phase, the framework design includes a set of guidelines for IT (Information Technology) systems that facilitate the construction of individual elements and the creation of communication interfaces. In subsequent stages, the framework may already implement elements of the access and communication program interface, as well as guidelines for the industrial components to be included. The proposed framework for additive technologies is based on modern IT tools that enable the creation of geographically and functionally possible prototyping systems that can be integrated into the structure of Industry 4.0. To create optimal processes and economic systems, the principles of the construction and integration of individual services and equipment were developed. This new comprehensive approach is proposed in the present paper as a coherent framework. Moreover, the proposed solution has great potential for use in the design and production processes of various industries, such as chemicals, materials and construction.

The aim of this contribution is to analyse practical aspects of the use of REST APIs and gRPC to realize communication tasks in applications in microservice-based ecosystems. On the basis of performed experiments, classes of communication tasks, for which given technology performs data transfer more efficiently, have been established. This, in turn, allows formulation of criteria for the selection of appropriate communication methods for communication tasks to be performed in an application using microservices-based architecture.

Examples of applications of the Industry 4.0 concept in manufacturing operations connected with processing of polymer materials were presented. Implementation of Industry 4.0 structure aims at increasing the speed of manufacturing with simultaneous decrease in the number of defective products. Such results are enabled by the use of integrated information systems coupled with automated manufacturing and quality control processes. On the basis of literature and own experience, it was found that the processing industry requires the use of such integrated systems, and further improvement of competitiveness will be difficult to achieve without implementing the developed Industry 4.0 concepts.

Continuous, real-time monitoring of occupational health and safety in high-risk workplaces such as construction sites can substantially improve the safety of workers. However, introducing such systems in practice is associated with a number of challenges, such as scaling up the solution while keeping its cost low. In this context, this work investigates the use of an off-the-shelf, low-cost smartwatch to detect health issues based on heart rate monitoring in a privacy-preserving manner. To improve the smartwatch’s low measurement quality, a novel, frugal machine learning method is proposed that corrects measurement errors, along with a new dataset for this task. This method’s integration with the smartwatch and the remaining parts of the health and safety monitoring system (built on the ASSIST-IoT reference architecture) are presented. This method was evaluated in a laboratory environment in terms of its accuracy, computational requirements, and frugality. With an experimentally established mean absolute error of 8.19 BPM, only 880 bytes of required memory, and a negligible impact on the performance of the device, this method meets all relevant requirements and is expected to be field-tested in the coming months. To support reproducibility and to encourage alternative approaches, the dataset, the trained model, and its implementation on the smartwatch were published under free licenses.

Background. Fat mass and obesity-associated gene (FTO) polymorphism remains the strongest known genetic determinant of common obesity. However, its influence depends on ethnicity, and the FTO-mediated predisposition to other metabolic disturbances is questionable. Objectives. The aim of our study was to evaluate the association between FTO rs9939609 polymorphism and metabolic syndrome in a population of Prospective Urban Rural Epidemiology (PURE) study in Poland. Material and methods. We enrolled 1,097 participants of the PURE study (683 women and 414 men) from the Lower Silesian voivodeship. Anthropometrical parameters and blood pressure were measured. Blood samples were taken for an examination of lipid profile and fasting glucose level. Genomic DNA was isolated and FTO polymorphism rs9939609 was genotyped. Results. Male A-allele carriers had significantly higher mean body mass, body mass index (BMI), waist-to-hip ratio (WHR), and waist and hip circumferences than men without risk allele. They were also more often diagnosed with obesity on the basis of BMI and central obesity parameters. No such influence was observed in women. There were no significant associations between FTO polymorphism and metabolic syndrome or its components. Conclusions. Our results suggest a sex-specific association between FTO polymorphism and obesity traits. The occurrence of metabolic syndrome or its components was not related with FTO gene variation in our cohort.