This case study deals with the design of a hybrid system for the prevention of thermal events in mining waste disposal sites and landfills. The overall design, real implementation, optimization and experimental verification of the functionality of the entire system are described in detail. Both experimental platforms are built on the Internet of Things (LoRaWAN and Sigfox) basis and meet the conditions for autonomous long-term on-site monitoring. The data collected is periodically transmitted wirelessly to a database repository, which processes relevant parameters for the operators of dispatching workplaces. The study is focused on a combination of surface and depth measurement methods. The experimental results clearly confirm the functionality of the proposed solutions, which will enable timely interventions and elimination of underground and surface combustions. Thanks to centralized data collection, a unique database has also been created, which can be used for the implementation of prediction algorithms (based, for example, on machine learning or artificial intelligence).

The analysis of biomedical signals is a very challenging task. This review paper is focused on the presentation of various methods where biomedical data, in particular vital signs, could be monitored using sensors mounted to beds. The presented methods to monitor vital signs include those combined with optical fibers, camera systems, pressure sensors, or other sensors, which may provide more efficient patient bed monitoring results. This work also covers the aspects of interference occurrence in the above-mentioned signals and sleep quality monitoring, which play a very important role in the analysis of biomedical signals and the choice of appropriate signal-processing methods. The provided information will help various researchers to understand the importance of vital sign monitoring and will be a thorough and up-to-date summary of these methods. It will also be a foundation for further enhancement of these methods.

The article describes the development and implementation of a complex monitoring system for measuring the concentration of carbon dioxide, ambient temperature, relative humidity and atmospheric pressure. The presented system was installed at two locations. The first was in the rooms at the Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava. The second was in the classrooms of the Grammar School and Secondary School of Electrical Engineering and Computer Science in Frenštát pod Radhoštěm. The article contains a detailed description of the entire measurement network, whose basic component was a device for measuring carbon dioxide concentration, temperature and relative humidity in ambient air and atmospheric pressure via wireless data transmission using IQRF^® technology. Measurements were conducted continuously for several months. The data were archived in a database. The article also describes the methods for processing the data with statistical analysis. Carbon dioxide concentration was selected for data analysis. Data were selected from at least two different rooms at each location. The processed results represent the time periods for the given carbon dioxide concentrations. The graphs display in percent how much of the time students or employees spent exposed to safe or dangerous concentrations of carbon dioxide. The collected data were used for the future improvement of air quality in the rooms.

Autonomous Monitoring System for Measurement of Parameters of Heat Collection Technology at Thermal Active Mining Dumps