This paper presents a system for measuring the geometry of powered roof support sections (Shield Support Monitoring System, SSMS). The problem of measuring the geometry of powered roof support sections for the purpose of predicting geological hazards during the rock excavation process is presented. Information on the construction and implementation of the SSMS and research at the Budryk Mine is included. The research aimed to evaluate both the precision and accuracy of the measurement apparatus created, as well as to examine how operating conditions affect the system’s usability. An analysis of inclinometer measurement errors in the prototype system was conducted during in situ tests, demonstrating minimal scattering and high sensor accuracy according to the provided data.

This article presents a proposal for a wireless diagnostic system for checking the air tightness of the ventilation network. The solution is designed to increase crew safety in underground mining plants and increase the energy efficiency of the ventube ventilation system. The system is based on sensors measuring the pressure inside the ventilation duct in relation to the barometric pressure in the immediate vicinity of the duct. The flow of diagnostic data is based on a cascade transfer. The data from the first sensor are transferred successively to the last one. Based on the prior calibration of alarm thresholds in each device, the leakage or factor influencing the increase of air flow resistance is located. The article presents the genesis of the creation and discusses the principle and purpose of the system. In the following chapters, the progress of work related to testing the system in laboratory, industrial, and underground conditions at the Velenje Premogovnik mine (Slovenia) is presented. The authors analyze the test results and indicate the directions of possible further work on improving the system. The proposed leak detection system is based on a network of pressure sensors that communicate with each other to clearly pinpoint the leak location. The system has been designed for operation in underground mining plants with limited space.

Mining in underground plants is associated with high risk. Improving work safety and increasing the productivity of longwall systems in the mining industry is a problem considering many criteria. Safety aspects concern both the crew and the machinery. The KOMAG Institute of Mining Technology designed and manufactured a geometry monitoring system based on inclinometers that meet the requirements of the ATEX directive. Monitoring of the roof support geometry is used for the prevention of loss of roof stability: roof fall or/and cave-in. The system was tested on a real object in real conditions.

This paper presents a concept of a routing algorithm for a network of sensors monitoring the condition of machinery and equipment operating in areas at risk of methane and/or coal dust explosion. It was assumed that the proposed algorithm would find application in sensor networks monitoring, among other things, oil pressure in powered roof supports and the position of powered roof support elements. The results of a literature analysis were presented, which included the simulation of sensor network routing algorithms, including, among others, reactive algorithms, proactive algorithms and algorithms based on so-called swarm intelligence (SI). As a result of the analyses, several algorithms were selected and implemented in a prototype sensor network. The characteristics of each of these algorithms are described. The article includes a description of the commissioning work of the network, which consisted of between 3 and 30 nodes. An analysis of the collected measurement data obtained for each criterion of the performance evaluation of the routing algorithms is presented.

Maintaining stable and reliable working conditions is a matter of vital importance for various companies, especially those involving heavy machinery. Due to human exhaustion, as well as unpredicted hazards and dangerous situations, the personnel has to take actions and wisely plan each move. This paper presents a human–computer interaction (HCI)-based system that uses a concentration level measurement function to increase the safety of machine and equipment operators. The system has been developed in response to the results of user experience (UX) analyses of the state of occupational safety, which indicate that the most common cause of accidents is the so-called insufficient concentration while performing work. The paper presents the reasons for addressing this issue and a description of the proposed electroencephalography (EEG)-based solution in the form of a concentration measurement system concept. We discuss in-field measurements of such a prototype solution, together with an analysis of obtained results. The method of implementing a wireless communication interface is also provided, along with a visualization application.

Intelligent routing algorithms in the complex sensors network possible to be used for construction of intelligent cells and energy storage are presented. The concept of Internet of Things (IoT) assumes connecting the possible highest number of objects (devices, machines, sensors, etc,), present in the given work environment, to ICT network to increase volume and quality of acquired data. Taking into account more common use of energy storages consisting of high number of secondary cells, supervised by BMS, the authors presented the concept of the intelligent cell equipped with voltage and temperature sensors, passive balancing system and a wireless communication system enabling the connection with the network of mesh topology. Due to that, construction and supervision of big energy storage will be significantly simplified. Self-organization and multi-redundant communication network will secure operational reliability, flexible configuration and operational safety. In the presented analysis of intelligent routing algorithms, information on the requirements put to them (in relation to e.g. number of nods, energy saving, work environment) is included. The results of analyses are summarized as well as directions of further research work on implementation of the selected solutions in the sensors network controlling the cells and energy storage operation, are indicated.