Accurate positioning information is a central step in the process of increasing automation and digitalization in the mining industry. Underground mine environments are prime examples for GNSS-denied environments that pose several additional challenges for the employed indoor positioning system (IPS). This work presents an ultra-wideband (UWB)–based system specifically tailored for underground mine environments. Initially, the UWB technology is reviewed and basic concepts of IPS are explained. Both software and hardware are described in detail, including positioning algorithms, electrical circuitry, and the mining-compatible enclosure. Finally, the results from field tests in an underground mine are presented and positioning performance and the influence of dilution of precision (DOP) on positioning results are empirically evaluated. The results show that the localization errors are mostly below 1 m. Individual zones of high localization errors are suspected to be caused by noise interference. Significant DOP influence due to the mining drift geometry can be confirmed. The system shows promising localization results for different mining applications, while influences negatively impacting the accuracy are presented as items for future research.

As indoor positioning provides particular challenges due to the unavailability of GPS signals, various systems such as ultra-wideband (UWB), radio frequency identification (RFID), ultrasound, and wireless local area network (WLAN) have been proposed in recent years. Some of these technologies are currently being marketed and some are still being developed. UWB technology allows for higher precision while also reducing power consumption. Hence, the underground automation and localization systems can use this technology for more accuracy and robustness. This article discusses new robust UWB modules used for underground positioning and collision avoidance with regard to human safety in underground mining operations.

The advent of digital mining has become a tangible reality in recent years. This digital evolution requires a predictive understanding of key elements, particularly considering the reliable communication infrastructures needed for autonomous machines. The LoRa technology and its underground propagation behavior can make an important contribution to this digitalization. Since LoRa operates with a high signal budget and long ranges in sub-GHz frequencies, its behavior is very promising for underground sensor networks. The aim of the development and series of measurements was to observe LoRa’s applicability and propagation behavior in active salt mines and to detect and identify effects arising from the special environment. The propagation of LoRa was measured via packet loss and signal strength in line-of-sight and non-line-of-sight configurations over entire mining sections. The aim was to analyze the performance of LoRa at the macroscopic level. LoRa operated at 868 MHz in the free band, and units were equipped with omni-directional antennas. The K+S Group’s active salt and potash mine Werra, Germany, was kindly opened as a distinctive experimental setting. The LoRa exhibited characteristics that were highly distinctive in this environment. The presence of the massive salt allowed the signal to bounce along drift edges with near-perfect reflection, which enabled travel over kilometers due to a waveguide-like effect. A packet loss of below $15\%$ showed that LoRa communication was possible over distances exceeding 1000 m with no line-of-sight in room-and-pillar structures. Measured differences of $\Delta 50\mathrm{dBm}$ values confirmed consistent path loss across different materials and tunnel geometries. This effect occurs due to the physical structure of the mining drifts, facilitating the containment and direction of signals, minimizing losses during propagation. Further modeling and measurements are of great interest, as they indicate that LoRa can achieve even better outcomes underground than in urban or indoor environments, as this waveguide effect has been consistently observed.

This paper presents the development of a monitoring system using acoustic emission (AE) analysis for the prediction of micro- and initial cracks in fatigue-stressed steel structures such as bridges, cranes, offshore, or industrial constructions. Initial experimentation suggests a relationship between microscopically observed crack length and AE intensity, further data is required to establish a definitive correlation. As part of an ongoing research project, AE measurement techniques and evaluation are to be further developed to create a monitoring concept for micro-crack prediction in more complex fatigue-stressed steel components. The focus of this research is not on the localization and detection of crack growth or structural changes but on micro-crack detection using AE. Existing acoustic emission analysis systems can thus be extended to measure and detect micro-cracks for the earliest possible identification of damage events. This paper describes the first results of the innovative research idea.

In the transition towards digitalization and automation of mining processes, high vol-umes of data are generated, including data from distributed sensor and actuator networks, voice communications, videos and vehicle telemetry data. This generated data is prepro-cessed on-site and subsequently transferred not only to headquarters for detailed analysis but also between mining machines and vehicles in case of automation or autonomous mining. Stable and efficient communication in the mining industry and particularly in underground environments is essential for increasing safety and productivity, support fast and secure transportation and facilitate logistical processes, ensuring continuous and smooth operations. Several different communication technologies and protocols exist related to the mining field, each with its unique characteristics, advantages, or limitations. This article focuses on two essential technologies that, despite their shared goal of enhancing communication networks, exhibit notable contrasts in some of their characteristics: Long Range (LoRa) as an existing technology in the industry since years and the technology of the fifth genera-tion (5G) of cellular network will be presented and discussed in this article, highlighting the significant differences in their properties and applications. This provides an important basis for understanding the limits and possible trade-offs of the wireless communication technologies required in the mining industry for large scale sensor networks.

Digital mining has become a tangible reality in recent years and the digital revolution enables and requires data exchange for autonomous machines and operational flow management. LoRa technology and its underground propagation behavior can make an important contribution to this digitalization. This paper presents a Data Mule approach that enabled progress in digitalization at refueling stations in active underground mining areas of a mine near Werra, Germany, operated by the K+S Group. This demonstration aimed to automate manual data collection at fuel gauges by using a dynamic LoRa network. We used specially developed LoRa Data Mule modules for operations over many square kilometers. LoRa was chosen for its industrial functionality and long-range capabilities, particularly in underground environments. The Data Mule modules used were in-house-designed units with underground mining-rated casing and connectors, as well as commercial LoRa boards and custom communication protocols. Connectivity between all systems was realized at travel speeds of 20 to 40 km/h, with connection data successfully relayed for 180 to 770 m, despite 90° turns and no line of sight. It was shown that the LoRa Data Mule approach can be used in a network of remote but active data generation points.