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LiDAR technology introduced the possibility of indirectly estimating various tree parameters. In 2020, Apple incorporated LiDAR sensors into their iPhone 12 Pro. This brings an opportunity to make data collection and plot scanning incredibly convenient. The main aim is to search for a tool and software to estimate the most accurate Diameter at Breast Height (DBH) for individual trees. Therefore, this study focuses on using an iPhone 12 Pro for data collection of individual trees. The performance of three software tools (ForestScanner, rTLS, RANSAC) for the estimation of DBH with field-estimated DBH was compared. The investigation of the significance of the estimation of DBH for each tree species was performed using the three algorithms. In this context, the scanning of 123 trees comprising six species: pine, oak, beech, hornbeam, spruce, and fir was done. DBH was estimated of the scanned tree point cloud using a built-in algorithm of ForestScanner application in the iPhone 12 Pro, RANSAC (CloudCompare plugin), and rTLS (an R-based package). In this study, ForestScanner showed the best results. Therefore, ForestScanner can be used as a reliable tool for measuring DBH. Inferences confirmed by ANOVA and Tukey post-hoc tests show that species significantly influence DBH. Accurate DBH estimation is crucial, and using lightweight devices like the iPhone can revolutionize the forest inventory sector in terms of the estimation of DBH. [ABSTRACT FROM AUTHOR]

Recently, UWB-based technology providing centimeter-level accuracy has been developed and widely utilized in indoor real-time location tracking systems. However, location accuracy varies due to factors such as frequency interference, collisions, reflected signals, and whether line-of-sight (LOS) conditions are met, and it can be challenging to ensure high accuracy in specific environments. Fortunately, when anchor positions are fixed, the locations of large obstacles such as columns or furniture remain relatively stable, leading to similar patterns of positioning bias at specific points. This study proposes an algorithm that corrects inaccurate positioning to more closely reflect the actual location based on bias and deviation maps generated using natural neighbor interpolation. Initially, positioning bias and deviations at specific points are sampled, and bias and deviation maps are created using natural neighbor interpolation. During location tracking, the algorithm detects candidate clusters and determines the centroid to estimate the actual location by applying the bias and deviation maps to the measured positions derived through trilateration. To validate the proposed algorithm, experiments were conducted in a non-LOS (NLOS) indoor environment. The results demonstrate that the proposed algorithm can reduce the positioning bias of a UWB-based RTLS by approximately 71.34% compared to an uncalibrated system. [ABSTRACT FROM AUTHOR]

Ultra wide band (UWB) based localization has been extensively utilized in indoor and urban dense regions which enables centimeter-level localization accuracy over global positioning system (GPS). However, the prior UWB-based localization methods still lack better localization accuracy and there is increase anchor deployment cost. Multiple input multiple output (MIMO) was created to improve wireless data transfer, but its ability to leverage many antennas for spatial information has resulted in localization and tracking applications. For this reason, the researchers incorporated MIMO in the UWB to improve the performance of the localization system. Yet, there are limitations to guaranteeing communication dependability while using poor localization approaches. To address the issues in the existing works, we proposed UWB-collaborative localization (UWB-CollLoc) method. Initially, the optimal placement of anchor nodes in the UWB MIMO environment is done to mitigate the accuracy issues by static non-line of sight (NLOS) blockages. The optimal placement is done by utilizing the smart crow search optimization (SCSO) algorithm which optimally places the anchor nodes by ensuring several metrics. Before localizing unlocalized mobile orphan tags, the available line of sight (LOS) anchors and Sub-anchors in the environment are detected using lightweight attention network (LAN) by the mobile orphan tags by considering several LOS and NLOS-related metrics. After determining the LOS anchors and sub-anchors, collaborative localization is done to improve localization efficiency, reduce the new anchor deployment cost, and mitigate the errors caused by dynamic NLOS blockages. The time difference of arrival (TDoA) and Angle of Arrival (AoA)-based collaborative localization is employed to reap the complete advantages of multilateration and angulation techniques in which the already localized mobile tags act as sub-anchors for unlocalized mobile orphan tags. Finally, the correctness of the localization results is ensured by forwarding the results to the UWB Real-Time Location System (UWB-RTLS) server which validates the results using the Jaccard similarity measure. The proposed work is experimented with in the Network Simulator Version-3.26 (NS-3.26) tool and compared with existing works in terms of several validation metrics. The results show that the proposed work outperforms better than the existing works. The experimental result shows that the proposed method has number of transmitted packets (26), LOS accuracy (0.79), NLOS accuracy (0.9), and correct rate (0.905). [ABSTRACT FROM AUTHOR]

In order to reduce the accident risk in road construction and maintenance, this paper proposes a novel solution for road-worker safety based on an untethered real-time locating system (RTLS). This system tracks the location of workers in real time using ultra-wideband (UWB) technology and indicates if they are in a predefined danger zone or not, where the predefined safe zone is delimited by safety cones. Unlike previous works that focus on road-worker safety by detecting vehicles that enter into the working zone, our proposal solves the problem of distracted workers leaving the safe zone. This paper presents a simple-to-deploy safety system. Our UWB anchors do not need any cables for powering, synchronisation, or data transfer. The anchors are placed inside safety cones, which are already available in construction sites. Finally, there is no need to manually measure the positions of anchors and introduce them to the system thanks to a novel self-positioning approach. Our proposal, apart from automatically estimating the anchors' positions, also defines the limits of safe and danger zones. These features notably reduce the deployment time of the proposed safety system. Moreover, measurements show that all the proposed simplifications are obtained with an accuracy of 97%. [ABSTRACT FROM AUTHOR]

In today's competitive landscape, manufacturing companies must embrace digital transformation. This study asserts that integrating Internet of Things (IoT) technologies for the deployment of real-time location systems (RTLS) is crucial for better monitoring of critical assets. Despite the challenge of selecting the right technology for specific needs from a wide range of indoor RTLS options, this study provides a solution to assist manufacturing companies in exploring and implementing IoT technologies for their RTLS needs. The current academic literature has not adequately addressed this industrial reality. This paper assesses the potential of Passive UHF RFID-RTLS in Industry 5.0, addressing the confusion caused by the emergence of new 'passive' RFID solutions that compete with established 'active' solutions. Our research aims to clarify the real-world performance of passive RTLS solutions and propose an updated classification of RTLS systems in the academic literature. We have thoroughly reviewed both the academic and industry literature to remain up to date with the latest market advancements. Passive UHF RFID has been proven to be a valuable addition to the RTLS domain, capable of addressing certain challenges. This has been demonstrated through the successful implementation in two industrial sites, each with different types of tagged objects. [ABSTRACT FROM AUTHOR]

Real Time Locating Systems (RTLS) and Radio Frequency Identification (RFID) are key technologies in asset tracking and management. Although they may look similar at first glance, they have different characteristics, advantages and disadvantages that make them suitable for different applications. [ABSTRACT FROM AUTHOR]

Real-Time Locating Systems (RTLS) have become an important supporting technology in manufacturing due to safety, logistical and managerial concerns. RTLS is a very wide term covering many different specific technologies. To increase the potential for implementation and better anticipate the costs associated, four different RTLS technologies have been evaluated according use case characteristics, maintenance costs, communication requirements. Data server capabilities, scalability, and integrability. The ability to analyze and determine such criteria are vital to support the selection of a specific technology (or mix of technologies) within manufacturing. The paper offers researchers and managers a reference comparison of the total costs surrounding the ownership of Ultra-wide band (UWB), Bluetooth Low Energy, Ultrasonic, and Optical RTLS technologies. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) for smart industry requires the surveillance and management of people and objects. The ultra-wideband positioning system is an attractive solution for achieving centimeter-level accuracy in target location. While many studies have focused on improving the accuracy of the anchor coverage range, it is important to note that in practical applications, positioning areas are often limited and obstructed by furniture, shelves, pillars, or walls, which can restrict the placement of anchors. Furthermore, some positioning regions are located beyond anchor coverage, and a single group with few anchors may not be able to cover all rooms and aisles on a floor due to non-line-of-sight errors causing severe positioning errors. In this work, we propose a dynamic-reference anchor time difference of arrival (TDOA) compensation algorithm to enhance accuracy beyond anchor coverage by eliminating local minima of the TDOA loss function near anchors. We designed a multidimensional and multigroup TDOA positioning system with the aim of broadening the coverage of indoor positioning and accommodating complex indoor environments. By employing an address-filter technique and group-switching process, tags can seamlessly move between groups with a high positioning rate, low latency, and high accuracy. We deployed the system in a medical center to locate and manage researchers with infectious medical waste, demonstrating its usefulness for practical healthcare institutions. Our proposed positioning system can thus facilitate precise and wide-range indoor and outdoor wireless localization. [ABSTRACT FROM AUTHOR]

In order to maintain competitiveness, it is essential for modern industrial companies to record as much data as possible, by processing which they can obtain valuable information for the development and optimization of production and logistics processes. The RTLS system provides an opportunity to perform this task. RTLS, or Real Time Location System, is a Real-Time Local Positioning System used to identify people and moving objects and to determine and continuously track their current position in a configurable space. Real-time positioning can help us to locate the position of objects and people inside the building. The paper presents and compares the relevant RTLS systems used in practice. In addition, the implementation process of an RTLS system created at the Institute of Logistics is described, as well as its application potential in relation to a case study developed. The abstract contains a short, general description of the topic and the research shown in the paper. [ABSTRACT FROM AUTHOR]

BACKGROUND: Navigation portable applications have largely grown during the last years. However, the majority of them works just for outdoor positioning and routing, due to their architecture based upon Global Positioning System signals. Real-Time Positioning System intended to provide position estimation inside buildings is known as Indoor Positioning System (IPS). OBJECTIVE: This paper presents an IPS implemented as a mobile application that can guide patients and visitors throughout a healthcare premise. METHODS: The proposed system exploits the geolocation capabilities offered by existing navigation frameworks for determining and displaying the user's position. A hybrid mobile application architecture has been adopted because it allows to deploy the code to multiple platforms, simplifying maintenance and upgrading. RESULTS: The developed application features two different working modes for on-site and off-site navigation, which offer both the possibility of actual navigation within the hospital, or planning a route from a list of available starting points to the desired target, without being within the navigable area. Tests have been conducted to evaluate the performance and the accuracy of the system. CONCLUSION: The proposed application aims to overcome the limitations of Global Navigation Satellite System by using magnetic fingerprinting in combination with sensor fusion simultaneously. This prevents to rely on a single technology, reducing possible system failures and increasing the scalability. [ABSTRACT FROM AUTHOR]

When introducing new technologies, companies are repeatedly faced with choosing between solutions from different providers. Regardless of all the good technical characteristics of the technology, if it is chosen inappropriately, it can prove to be a cost driver instead of something that brings added value to the system. Aware of this, we considered selecting a real-time location system (RTLS) based on Ultra-wideband technology in the indoor work environment. In practice and theory, it has been proven that the introduction of the RTLS can have highly positive effects on performance and business sustainability indicators. When reviewing the literature, it was noticed that authors solely focus on the technical properties of the systems and prices when giving guidelines on selecting the optimal RTLS. This article aims to provide advanced guidelines for UWB RTLS selection, proposing a phased selection process which is the main novelty proposed and investigated in this research. The guidelines are based on fragmented recommendations in the scientific literature that have been identified, gathered, considered, and reasonably allocated to the advanced performance-oriented phased selection process. In practice, this approach enables decision-makers to choose the most efficient and most appropriate UWB RTLS for specific logistics systems. [ABSTRACT FROM AUTHOR]

In recent years, the IoT has emerged as the most promising technology in the key evolution of industry 4.0/industry 5.0, smart home automation (SHA), smart cities, energy savings and many other areas of wireless communication. There is a massively growing number of static and mobile IoT devices with a diversified range of speed and bandwidth, along with a growing demand for high data rates, which makes the network denser and more complicated. In this context, the next-generation communication technology, i.e., sixth generation (6G), is trying to build up the base to meet the imperative need of future network deployment. This article adopts the vision for 6G IoT systems and proposes an IoT-based real-time location monitoring system using Bluetooth Low Energy (BLE) for underground communication applications. An application-based analysis of industrial positioning systems is also presented. [ABSTRACT FROM AUTHOR]

Value stream mapping (VSM) is a valuable practice employed by industry experts to identify inefficiencies in the value chain due to its visual representation capability and general ease of use. VSM supports the visualization of product and material flows as a snapshot and enhances understanding of production behavior across multiple domains; however, it can lead to oversimplification, tedious/inaccurate data collection, and can have a static nature. Through improved digital integration this paper presents a semiautomated VSM solution that leverages dynamic Real Time Location System (RTLS) data to track motion throughout a production floor. This solution incorporates a high precision UWB RTLS, that allows for the real-time analysis and formulation of different state maps to track processes, equipment, people, and materials on the manufacturing floor. This multi-state mapping outcome has demonstrated the ability to allow for the rapid comparisons of various state maps and supports more effective and robust decision making. Based on initial results the system was able to continuously map accurate and reliable shop floor data and update new maps with limited human intervention, demonstrating the ability for RTLS to enhance VSM. [ABSTRACT FROM AUTHOR]

In semi-automated manufacturing, an increasing amount of intelligent mobile robots operate in close proximity to human workers. Considering future positions of humans allows to further improve the efficiency in terms of throughput of Autonomous Mobile Robots (AMR) and Automated Guided Vehicles (AGV). The longer the prediction horizon, i.e. the more position values of humans can be predicted in the near and distant future, the more a robot can adjust its route accordingly and optimize the process. This paper discusses the challenges of human motion trajectory prediction in manufacturing and presents a schedule-based approach that uses real-time schedule data obtained from Manufacturing Execution Systems (MES). Schedule-awareness in human motion trajectory prediction extends semantic mapping approaches and effectively reduces the number of probable destinations by considering which process steps are next for the currently produced goods. With a reduced set of destinations, the performance of forward-planning trajectory prediction can be improved. For evaluation, a commercial MES is used together with an Ultra-wideband-based Real-Time Locating System (RTLS) for obtaining position data of humans. On this basis, a naive Bayes classifier utilizes MES-schedule and real-time position data to predict human motion intentions. Abstract activity modeling ensures that only a few training data sets are required for deployment, thus making this approach suitable for rapidly changing manufacturing environments such as in flexible manufacturing. [ABSTRACT FROM AUTHOR]

This work presents a novel landing assistance system (LAS) capable of locating a drone for a safe landing after its inspection mission. The location of the drone is achieved by a fusion of ultra-wideband (UWB), inertial measurement unit (IMU) and magnetometer data. Unlike other typical landing assistance systems, the UWB fixed sensors are placed around a 2 × 2 m landing platform and two tags are attached to the drone. Since this type of set-up is suboptimal for UWB location systems, a new positioning algorithm is proposed for a correct performance. First, an extended Kalman filter (EKF) algorithm is used to calculate the position of each tag, and then both positions are combined for a more accurate and robust localisation. As a result, the obtained positioning errors can be reduced by 50% compared to a typical UWB-based landing assistance system. Moreover, due to the small demand of space, the proposed landing assistance system can be used almost anywhere and is deployed easily. [ABSTRACT FROM AUTHOR]

Staff-to-staff transmission of SARS-CoV-2 poses a significant risk to the Emergency Department (ED) workforce. We measured close (<6 ft), prolonged (>10 min) staff interactions in a busy pediatric Emergency Department in common work areas over time as the pandemic unfolded, measuring the effectiveness of interventions meant to discourage such close contact. We used a Real-Time Locating System to measure staff groupings in crowded common work areas lasting ten or more minutes. We compared the number of these interactions pre-pandemic with those occurring early and then later in the pandemic, as distancing interventions were suggested and then formalized. Nearly all healthcare workers in the ED were included, and the duration of interactions over time were evaluated as well. This study included a total of 12,386 pairs of staff-to-staff encounters over three time periods including just prior to the pandemic, early in the pandemic response, and later in the steady-state pandemic response. Pairs of staff averaged 0.89 high-risk interactions hourly prior to the pandemic, and this continued early in the pandemic with informal recommendations (0.80 high-risk pairs hourly). High-risk staff encounters fell significantly to 0.47 interactions per hour in the steady-state pandemic with formal distancing guidelines in place and decreased patient and staffing volumes. The duration of these encounters remained stable, near 16 min. Close contact between healthcare staff workers did significantly decrease with formal distancing guidelines, though some high-risk interactions remained, warranting additive protective measures such as universal masking. [ABSTRACT FROM AUTHOR]

In the last decade, smart textiles have become very popular as a concept and have found use in many applications, such as military, electronics, automotive, and medical ones. In the medical area, smart textiles research is focused more on biomonitoring, telemedicine, rehabilitation, sport medicine or home healthcare systems. In this research, the development and localization accuracy measurements of a smart T-shirt are presented, which will be used by elderly people for indoor localization in ambient assisted living applications. The proposed smart T-shirt and the work presented is considered to be applicable in cases of elderly, toddlers or even adults in indoor environments where their continuous real-time localization is critical. This smart T-shirt integrates a localization sensor, namely the Localino sensor, together with a solar panel for energy harvesting when the user is moving outdoors, as well as a battery/power bank that is both connected to the solar panel and the Localino sensor for charging and power supply respectively. Moreover, a mock-up house was deployed, where the Localino platform anchors were deployed at strategic points within the house area. Localino sensor nodes were installed in all the house rooms, from which we obtained the localization accuracy measurements. Furthermore, the localization accuracy was also measured for a selected number of mobile user scenarios, in order to assess the platform accuracy in both static and mobile user cases. Details about the implementation of the T-shirt, the selection and integration of the electronics parts, and the mock-up house, as well as about the localization accuracy measurements results are presented in the paper.

The Determining the current position of objects in logistics processes (products, unit loads, forklifts, etc.) is the basis for new process development and optimization opportunities (e.g., development of storage strategy, forklift route planning, etc.) that significantly affect the competitiveness of companies. Many technologies can be used for positioning, however most of them do not provide the required accuracy. The dissertation presents the most important basic concepts related to locationing, as well as the relevant technologies that can be used to determine the positions of logistics objects within the warehouse, together with their advantages and disadvantages. [ABSTRACT FROM AUTHOR]

Objective: Modern health care requires patients, staff, and equipment to navigate complex environments to deliver quality care efficiently. Real-time locating systems (RTLS) are local tracking systems that identify the physical locations of personnel and equipment in real time. Applications and analytic strategies to utilize RTLS-produced data are still under development. The objectives of this systematic review were to describe and analyze the key features of RTLS applications and demonstrate their potential to improve care delivery.Materials and Methods: We searched MEDLINE, SCOPUS, and IEEE following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Inclusion criteria were articles that utilize RTLS to evaluate or influence workflow in a healthcare setting. We summarized aspects of relevant articles, identified key themes in the challenges of applying RTLS to workflow improvement, and thematically reviewed the state of quantitative analytic methodologies.Results: We included 42 articles in the final qualitative synthesis. The most frequent study design was observational (n = 24), followed by descriptive (n = 12) and experimental (n = 6). The most common clinical environment for study was the emergency department (n = 12), followed by entire hospital (n = 7) and surgical ward (n = 6).Discussion: The focus of studies changed over time from early experience to optimization to evaluation of an established system. Common narrative themes highlighted lessons learned regarding evaluation, implementation, and information visibility. Few studies have developed quantitative techniques to effectively analyze RTLS data.Conclusions: RTLS is a useful and effective adjunct methodology in process and quality improvement, workflow analysis, and patient safety. Future directions should focus on developing enhanced analysis to meaningfully interpret RTLS data. [ABSTRACT FROM AUTHOR]

Forensic archaeology and the search for missing persons, not only reconstructions on the crime scene but also substantial help to find missing persons.

Real-time location systems (RTLS) allow a spatial and time related tracking of objects in their environment. An increasing number of technologies and providers are available nowadays. Besides applications in e.g. healthcare and general logistics, RTLS bear also interesting potentials in context of factories. Some manufacturing related use cases can already be found in research and industrial practice. While overcoming an isolated perspective on single solutions, this paper aims at providing a structured overview and common understanding on technological potentials and challenges. Based on that, a systematic design of RTLS based solutions is enabled. [ABSTRACT FROM AUTHOR]

Every year healthcare organizations suffer from several issues, such as unapropriated workflow, thousands of deaths caused by medical errors, counterfeit drugs, and increasing costs. To offer better patient care and increase profit, hospitals could adopt solutions that help remedy these problems. Real-Time Location Systems have the potential to deal with many of these issues, as well as offering means for developing new and intelligent solutions. This kind of system enables tracking assets and people, allowing several improvements. Even though the benefits of such solutions are well known and desired by healthcare providers, their large scale adoption is still distant. In this article, we surveyed Real-Time Location Systems usage in hospitals. While developing this survey, we observed a need for organizing important aspects of healthcare-oriented Real-Time Location Systems. Therefore, we analyzed challenges regarding this topic and a taxonomy proposed. This survey offers researchers and developers ways to comprehend the challenges surrounding this area while proposing a classification of aspects that a Real-Time Location System for healthcare environments must assess for it to be successful. [ABSTRACT FROM AUTHOR]

Forensic archaeology and the search for missing persons, not only reconstructions on the crime scene but also substantial help to find missing persons. [ABSTRACT FROM AUTHOR]

• Human poses and radio id fusion can create valuable activity recognition datasets. • Vision and radio devices data fusion enable assessing each technology limitation. • Body joints estimated with ToF devices enable radio tracking accuracy improvement. • Radiofrequency tracking errors can be reduced up to 46% through data fusion. Recent advances in the capabilities of computing devices enable new methods to estimate the pose of humans. Human pose estimation techniques are relevant for several industry fields, such as surveillance and interactive entertainment. Further, encoded human poses provide a valuable input for behavioral analysis and activity recognition. Body part detectors offer millimetric accuracy thanks to state-of-the-art Computer Vision technology. However, they still suffer from issues, such as long-term occlusion, that hinder the identification of human subjects. Such problems are intrinsic to Computer Vision devices and can only be solved either with the use of heuristic methods or the deployment of more cameras, which are not always feasible. In turn, radiofrequency-based tracking systems do not suffer from occlusion or identity loss problems and, albeit not as precise as Computer Vision methods, can achieve a high accuracy level. Radiofrequency positioning systems and human pose estimation techniques can complement each other in different ways. For example, the prior can help to identify tracked humans and reduce occlusion errors, while the later can increase the accuracy of obtained positions. Thus, the combination of radiofrequency-based positioning and computer vision-based human pose estimation yields a solution that provides better tracking results. Therefore, this article proposes a system that generates identified pose data by fusing the unique identities of radiofrequency sensors with unidentified body poses while using estimated body parts for reducing radiofrequency position estimations errors. Experiments with a proof-of-concept demonstrate the feasibility of the sensor fusion technique and also show a potential reduction on positioning errors by nearly 46%. [ABSTRACT FROM AUTHOR]

Purpose: An indoor, real‐time location system (RTLS) can benefit both hospitals and patients by improving clinical efficiency through data‐driven optimization of procedures. Bluetooth‐based RTLS systems are cost‐effective but lack accuracy because Bluetooth signal is subject to significant fluctuation. We aim to improve the accuracy of RTLS using the deep learning technique. Methods: We installed a Bluetooth sensor network in a three‐floor clinic building to track patients, staff, and devices. The Bluetooth sensors measured the strength of the signal broadcasted from Bluetooth tags, which was fed into a deep neural network to calculate the location of the tags. The proposed deep neural network consists of a long short‐term memory (LSTM) network and a deep classifier for tracking moving objects. Additionally, a spatial‐temporal constraint algorithm was implemented to further increase the accuracy and stability of the results. To train the neural network, we divided the building into 115 zones and collected training data in each zone. We further augmented the training data to generate cross‐zone trajectories, mimicking the real‐world scenarios. We tuned the parameters for the proposed neural network to achieve relatively good accuracy. Results: The proposed deep neural network achieved an overall accuracy of about 97% for tracking objects in each individual zone in the whole three‐floor building, 1.5% higher than the baseline neural network that was proposed in an earlier paper, when using 10 s of signals. The accuracy increased with the density of Bluetooth sensors. For tracking moving objects, the proposed neural network achieved stable and accurate results. When latency is less of a concern, we eliminated the effect of latency from the accuracy and gained an accuracy of 100% for our testing trajectories, significantly improved from the baseline method. Conclusions: The proposed deep neural network composed of a LSTM, a deep classifier and a posterior constraint algorithm significantly improved the accuracy and stability of RTLS for tracking moving objects. [ABSTRACT FROM AUTHOR]

The article presents tests on the possibility of using ultrasonic transducers for accurate distance measurement in hard coal mines. In order to check the impact of selected disturbing factors on the measurement results, test stands were built, and then a full cycle of measurements with the use of different transducers (AR30 and AR41), which were selected and pre-tested in previous research projects, was realized. The impact of such disturbing factors as airborne dust (coal, stone, lime and mixed dust), changes in temperature and humidity on the propagation of ultrasonic waves, amplitude and measurement accuracy was investigated. The tests were preceded by theoretical analysis. It was found that the transducers selected for the tests had a sufficient accuracy and range, so they can be used in the devices planned to be designed, allowing for the determining of the location of a roadheader in hard coal mine roadways, taking into account technical and legal restrictions. It was also specified which disturbing factors should be compensated and what methods and parameters of this compensation should be used.

W artykule przedstawiono ideę systemów typu RTLS pod kątem wykorzystania ich w celu eliminacji marnotrawstwa w procesie budowlanym. Opisywane systemy z punktu widzenia strumienia wartości są pomocne w wykrywaniu czynności niedodających wartości. Autorzy przedstawili temat w aspekcie formalno-prawnym związanym z monitorowaniem i śledzeniem pracowników podczas pracy. Zwrócono uwagę na niezbędne dokumenty, pozwolenia, zgłoszenia i zgody pracowników, które zgodnie z obowiązującym w Polsce prawem należy posiadać, aby móc wykorzystywać tego typu systemy do zbierania i przetwarzania danych o lokalizacji pracowników w trakcie wykonywania prac.

Human–robot collaboration is becoming ever more widespread in industry because of its adaptability. Conventional safety elements are used when converting a workplace into a collaborative one, although new technologies are becoming more widespread. This work proposes a safe robotic workplace that can adapt its operation and speed depending on the surrounding stimuli. The benefit lies in its use of promising technologies that combine safety and collaboration. Using a depth camera operating on the passive stereo principle, safety zones are created around the robotic workplace, while objects moving around the workplace are identified, including their distance from the robotic system. Passive stereo employs two colour streams that enable distance computation based on pixel shift. The colour stream is also used in the human identification process. Human identification is achieved using the Histogram of Oriented Gradients, pre-learned precisely for this purpose. The workplace also features autonomous trolleys for material supply. Unequivocal trolley identification is achieved using a real-time location system through tags placed on each trolley. The robotic workplace’s speed and the halting of its work depend on the positions of objects within safety zones. The entry of a trolley with an exception to a safety zone does not affect the workplace speed. This work simulates individual scenarios that may occur at a robotic workplace with an emphasis on compliance with safety measures. The novelty lies in the integration of a real-time location system into a vision-based safety system, which are not new technologies by themselves, but their interconnection to achieve exception handling in order to reduce downtimes in the collaborative robotic system is innovative.

Determining the location of objects, for example roadheader in a hard coal mine, is a task that should be automated in the conditions of state-of-the-art mining. Current solutions do not meet the user’s expectations due to the lack of the possibility of automation, maladjustment to the environment of a hard coal mine or not meeting the legal requirements. The article describes the initial stage of work on an automatic system for determining the position of machines in difficult underground conditions, including the analysis of requirements and constraints, an overview of available solutions, technologies and algorithms, as a result of which devices were selected for further tests. To determine the location, it is necessary to take distance measurements with high accuracy, despite the disturbances resulting from the working environment. Ultrasonic devices were selected and then tested under various operating conditions, including different distances between the transmitter and receiver as well as different directions and intensities of air movement that could distort the measurement results. During tests, sufficient accuracy, as well as other parameters, of the ultrasonic transducers were confirmed, allowing for distance measurements in the required range, suitable for use in the real-time locating system (RTLS) being developed.