Materiały konferencyjne SEP 2021

[37] P. Pyda, P. Stefaniak, H. Dudycz, Development assumptions of a data and service management centre at KGHM S.A., Min. Goes Digit. (2019) 569–577. https://doi.org/10.1201/9780429320774- 66. [38] P. Pyda, H. Dudycz, P. Stefaniak, A Model of Enterprise Analytical Platform for Supply Chain Management, in: M. Hernes, K. Wojtkiewicz, E. Szczerbicki (Eds.), Adv. Comput. Collect. Intell., Springer International Publishing, Cham, 2020: pp. 363–375. https://doi.org/10.1007/978-3-030- 63119-2_30. [39] C. Gellweiler, Types of IT Architects: A Content Analysis on Tasks and Skills, J. Theor. Appl. Electron. Commer. Res. 15 (2020) 15–37. https://doi.org/10.4067/S0718-18762020000200103. ABSTRACT In the era of Industry 4.0, technologies such as Big Data (BD) and the Internet of Things (IoT) play a crucial role, especially in the case of multi-plant production companies. For these com- panies, the challenge is collecting and processing massive amounts of data from industrial de- vices and extracting essential information from that data in real-time for ad hoc decision- making. The ability to analyze data from industrial devices translates directly into optimizing production processes, cost optimization, prevention of unplanned events, and safety at work. In this context, particular attention should be paid to the analytical platform, i.e., Big Data Analyt- ics (BDA), the primary source of the Industry Internet of Things - IIoT. The article presents the literature review results for using Big Data and IoT solutions for industry (mainly mining). Based on the analysis of a multi-plant mining enterprise, the main challenges faced by this type of company planning to implement BD and IoT technologies were identified. Finally, a case of using sensors to collect data on vital parameters and the location of workers in a mine is pre- sented.