Real-time Location System Research Articles

Current technologies and the applications of data analytics for crude oil leak detection in surface pipelines

Pipeline pressure monitoring has been the traditional and most popular leak detection approach, however, the delays with leak detection and localization coupled with the large number of false alarms led to the development of other sensor-based detection technologies. The Real Time Transient Model (RTTM) currently has the best performance metric, but it requires collection and analysis of large data volume which, in turn, has an impact in the detection speed. Several data mining (DM) methods have been used for leak detection algorithm development with each having its own advantages and shortcomings. Mathematical modelling is used for the generation of simulation data and this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the ANN and SVM require a large training dataset for development of accurate models, mathematical modelling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modelling for the development of a robust real time leak detection and localization system for surface pipelines. Several case studies are also presented.

ZigBee Technology to Provide Elderly People with Well-Being at Home

Background: The number of elderly people is growing, and it becomes a challenge for the families and governments regard their health. They are facing declines in their health and missing some of the quality of life that is provided to them. They are unable to control their self. They are vulnerable to fall and get in dangerous or restricted area. Aim: This study aims at conducing an experiment using Real-Time Location System (RTLS) via ZigBee technology in order to track the elderly person at his/her home. Objectives: To track the old age people and provide them proper care and support whenever they are in challenging times. Method: RTLS is a system that offers a real-time tracking and positioning of people or objects. Results: The results showed that the ZigBee technology provides valuable insights to determine the location of an elderly person at home and sends an alert when a person gets in a restricted area. Conclusion: ZigBee have contributed to be one of the best of its kind protocol that can help to track and mange old aged people at house.

Convolutional Neural Networks Refitting by Bootstrapping for Tracking People in a Mobile Robot

Convolutional Neural Networks are usually fitted with manually labelled data. The labelling process is very time-consuming since large datasets are required. The use of external hardware may help in some cases, but it also introduces noise to the labelled data. In this paper, we pose a new data labelling approach by using bootstrapping to increase the accuracy of the PeTra tool. PeTra allows a mobile robot to estimate people’s location in its environment by using a LIDAR sensor and a Convolutional Neural Network. PeTra has some limitations in specific situations, such as scenarios where there are not any people. We propose to use the actual PeTra release to label the LIDAR data used to fit the Convolutional Neural Network. We have evaluated the resulting system by comparing it with the previous one—where LIDAR data were labelled with a Real Time Location System. The new release increases the MCC-score by 65.97%.

Parity and days in milk affect cubicle occupancy in dairy cows

Modern dairy cattle farms are usually equipped with cubicle systems to provide cows with comfortable conditions for lying down and resting. Cows are free to choose any cubicle they want, but in reality, they do not distribute themselves uniformly throughout the barn. There are many factors that affect where a cow lies down, such as hierarchy of a cow, access to resources, cow traffic nearby, etc. In this study, we used real-time location system data from two commercial farms to examine patterns of cubicle occupancy in relation to parity and lactation stage. We summarized cubicle occupancy over several days and compared different areas of the barn. Our findings suggest that, in general, there was a higher occupancy of cubicles close to the feeding areas. High parity cows lay down more frequently in cubicles close to the milking area as opposed to first lactation cows that tend to occupy less busy areas of the barn. The overall conclusion is that cubicle occupancy is not uniform throughout the barn, and patterns related to parity and DIM are seen. This information can be important for future studies on spread of diseases and for management purposes.

PSXVI-20 Real-time localization system for dairy cattle in a commercial facility: Evaluation of dynamic positioning ability

Abstract Real-time location tracking of dairy cattle on commercial facilities enables producers to quickly locate and tend to cows and provides insight into health status and animal welfare. The effectiveness of these systems depends on accurate and reliable reporting of information. Therefore, this experiment’s objective was to assess the dynamic positioning abilities of a commercially available real-time location ear tag system (SmartBow; Zoetis, Parsippany, NJ) for use in group-housed dairy cattle. Using 2 pens of a freestall barn, cameras (n = 18) were installed on barn fixtures and positioned to photograph cow usage of feedbunk (n = 4), stall (n = 10), or waterer (n = 4). Photographs were captured automatically at 1-min intervals for 85 hours, consecutively. Laser measurements determined X and Y coordinates for reference point locations respective to camera. In dynamic position assessments, variations in ear tag proximity to measured reference points are to be expected. One trained observer reviewed photographs, saving only those depicting cows with visible farm-assigned ID. Data points were only defined if farm-assigned ID was associated with an active technology ear tag. For data analyses, technology-reported X and Y coordinates of data points were compared to reference point locations. Of all data points (n = 114,633), mean distance error was 3.82 m (SD= 6.73 m). Median distance error was 2.44 m (SD= 6.73; Q1= 1.41 m; Q3=5.13 m). With removal of outliers (99th percentile), data (n = 113,487) had a mean distance error of 3.82 m (min= 0.01 m; max= 33.80 m) and a median of 2.41 m (SD= 2.78 m; Q1= 1.40 m; Q3= 4.95 m). Using distance error, mean percentages of data points that fell within specified radii of circles centered about reference point locations were calculated (Table 1). These results suggest that this ear tag technology can accurately report the dynamic positions of dairy cattle moving freely in a commercial freestall barn environment.

The Use of Radio Frequency Identification Technologies for Preventing the Spread of Coronavirus

This article contains description of methods to prevent the spread of coronavirus using modern technologies. Businesses face significant challenges in complying with social distancing guidelines, and they do not have a real understanding of whether these guidelines are followed in their facilities. Many companies use Radio Frequency Identification (RFID) technology to ensure the safety of employees by tracking the proximity or location of each. Kinexon's SafeZone and Triax Proximity Trace are effective solutions to prevent the spread of coronavirus within the enterprise. SafeZone is a unique and powerful active RFID technology, the purpose of which is formation of a warning about the convergence and tracking of contacts in case of a positive test result for COVID-19. The solution consists of UWB labels, worn by employees, as well as cloud software to manage the collected data. Contact information allows companies to take steps to create a safe and healthy work environment. The SafeZone solution uses ultra-wideband (UWB) radio frequency tags. UWB uses the frequency bands 3.25 - 4.75 GHz and 6.25 - 6.75 GHz, which do not overlap with the bands of wireless networks (WLAN) and ISM. RTLS (Real-Time Locating Systems) - an automated system that provides identification, accumulation, processing and storage of information about the location and movement of people, objects, mobile machinery and vehicles to monitor technological and business processes, signaling, as well as for retrospective analysis of certain processes and situations. All RTLS systems consist of several main components: tags, readers and software for interpreting data. Use of active UWB tags in these systems allows to achieve high speeds at a distance of up to 10 m, the technology allows you to reach 110 Mbps. UWB module - a desktop device for setting up and accounting for UWB Tag devices. UWB hub - a device capable of performing thousands of scan scans per second at a distance of up to 30 cm. UWB Sensor - a device that detects pulses emitted by UWB tags and provides the exchange of operational information about resources. UWB reader is an access control device that uses the patented technology of short-pulse ultra-wideband (UWB) signals. UWB-tag - a device that can be attached to objects or clothing of personnel to track and track their location at any time in real time with incredible accuracy. Triax Proximity Trace technology provides active feedback, in the form of visual and audible signal, so people understand when they have violated the proper social distance. Due to Triax Proximity Trace it is possible to determine the degree of contact of employees with those who received a positive test, for example, according to the CDC classification. Components of the system: labels, gateways that are deployed in strategic places, cloud software and information panel for managing proximity event data. Triax Proximity Trace uses tags that operate at 900 MHz. Due to SafeZone and Triax Proximity Trace solutions the company can have a complete picture of potential patients and send for testing real contacts.

An Augmented Reality Symbiosis Software Tool for Sustainable Logistics Activities

Augmented Reality (AR) is an emerging technology in the Industry 4.0 and Logistics 4.0 contexts with an important role in man–machine symbiosis scenarios. Practitioners, although already acquainted with AR technology, are reluctant to adopt AR applications in industrial operations. This stems from the fact that a direct connection that is important for the management of sustainability goals is missing. Moreover, such a connection with economic, social, and environmental sustainability parameters sparsely appears in the AR literature. The proposed research, on one hand, presents an innovative architecture for a stable and scalable AR application that extents state-of-the-art solutions and, on the other hand, attempts to study AR technology within the framework of a sustainable business strategy. The developed system utilizes the Robot Operating System (ROS) alongside an AR mobile application to present an employee navigation scenario in warehouses and production lines. ROS is responsible for mapping the industrial facility, while the AR mobile application identifies the surrounding environment, along with a Real-Time Location System localizes employees in the facility. Finally, ROS identifies the shortest path between the employee and the destination point, while the AR mobile application presents the virtual path for reaching the destination.

Two-Dimensional Cartesian Coordinate System Educational Toolkit: 2D-CACSET.

Engineering education benefits from the application of modern technology, allowing students to learn essential Science, Technology, Engineering, and Mathematics (STEM) related concepts through hands-on experiences. Robotic kits have been used as an innovative tool in some educational fields, being readily accepted and adopted. However, most of the time, such kits’ knowledge level requires understanding basic concepts that are not always appropriate for the student. A critical concept in engineering is the Cartesian Coordinate System (CCS), an essential tool for every engineering, from graphing functions to data analysis in robotics and control applications and beyond. This paper presents the design and implementation of a novel Two-Dimensional Cartesian Coordinate System Educational Toolkit (2D-CACSET) to teach the two-dimensional representations as the first step to construct spatial thinking. This innovative educational toolkit is based on real-time location systems using Ultra-Wide Band technology. It comprises a workbench, four Anchors pinpointing , , , axes, seven Tags representing points in the plane, one listener connected to a PC collecting the position of the Tags, and a Graphical User Interface displaying these positions. The Educational Mechatronics Conceptual Framework (EMCF) enables constructing knowledge in concrete, graphic, and abstract levels. Hence, the students acquire this knowledge to apply it further down their career path. For this paper, three instructional designs were designed using the 2D-CACSET and the EMCF to learn about coordinate axes, quadrants, and a point in the CCS.

Integration and Prototyping of a Pulsed RF Oscillator with an UWB Antenna for Low-Cost, Low-Power RTLS Applications.

The goal of this paper is to present a compact low-cost and low-power prototype of a pulsed Ultra Wide Band (UWB) oscillator and an UWB elliptical dipole antenna integrated on the same Radio Frequency (RF) Printed Circuit Board (PCB) and its digital control board for Real Time Locating System (RTLS) applications. The design is compatible with IEEE 802.15.4 high rate pulse repetition UWB standard being able to work between 6 GHz and 8.5 GHz with 500 MHz bandwidth and with a pulse duration of 2 ns. The UWB system has been designed using the CST Microwave Studio transient Electro-Magnetic (EM) circuit co-simulation method. This method integrates the functional circuit simulation together with the full wave (EM) simulation of the PCB’s 3D model allowing fast parameter tuning. The PCB has been manufactured and the entire system has been assembled and measured. Simulated and measured results are in excellent agreement with respect to the radiation performances as well as the power consumption. A compact, very low-power and low-cost system has been designed and validated.

Providing proximity alerts to workers on construction sites using Bluetooth Low Energy RTLS

Construction is one of the most dangerous industrial sectors. Struck-by object or equipment is one of the main causes of fatal accidents on construction sites. Although many regulations have been designed for preventing struck-by accidents, they still happen and lead to many injuries and fatalities. The application of real-time location systems (RTLS) on construction sites provides new possibilities in construction safety management. Previous researchers have proposed using RTLS to track the locations of workers and equipment on construction sites to improve construction safety. However, they have the limitation of cabling problems. Also, providing effective safety alerts to workers within dangerous proximity to equipment has not been well addressed. This paper aims to develop a method for detecting the proximities as well as providing proximity safety alerts to workers on construction sites using Bluetooth Low Energy (BLE) RTLS. Here, vibro-tactile alerts representing different cases of proximities were defined. Unnecessary alerts were filtered out to avoid desensitizing workers. A number of tests were conducted on a construction site to test the prototype system developed based on the proposed method. The results indicate that the system is capable of detecting proximities and generating timely vibro-tactile alerts, which can be easily perceived by the workers.

Estimating Physical Work-Load on ED Clinicians and Staff Using Real-Time Location Systems

Clinicians' work pressure and burnout turned out as an important factor in modern hospitals which urges us to search for rapid and accurate methods to proxy the workload. By using RFID technology, we hope to monitor the physical pressure on the clinical staff of the emergency department (ED) at the Mayo Clinic Saint Mary's Hospital. The data collected will be used to determine the workload and pressure put on various staff members. A real-time location system (RTLS) has been used to monitor and track the movements of the hospital team and compute active vs. sedentary time for staff. Risk thresholds for the sedentary time from a previous study were utilized to visualize trends in staff sedentary time. Members of the ED team are under great stress at all times; we use RFID technology to get a better understanding of how much their work environment contributes to the pressure of their jobs.

Improving Care Delivery: Location Timestamps to Enhance Process Measurement of a Clinical Workflow.

We applied the FOCUS-Plan-Do-Check-Act framework to reduce the time from arrival to sedation for long-bone fractures. First, we added supplementary framework-defining steps to repeat the Clarifying and Understanding steps. We then extracted objective time-based data from an electronic health record (EHR) system and a real-time locating system (RTLS). We then compared and contrasted the findings of traditional surveys with analyses of timed steps within the sedation workflow. When identifying the source of delays, traditional survey techniques yielded ambiguous and even conflicting results based on clinical roles. The timestamps supported 5 measurable clinical role of subworkflows. By measuring the time to completion for 54 sedation cases, workflow patterns and significant bottlenecks were identified. Analyzing the time to complete individual tasks provided a more nuanced description of workflow delays and clarity when traditional survey results conflicted. Augmenting traditional QI process maps with EHR and RTLS timestamps better explained workflow bottlenecks, informing the QI team when selecting targets for subsequent Plan-Do-Check-Act work.

Development of a machine learning-based real-time location system to streamline acute endovascular intervention in acute stroke: a proof-of-concept study

BackgroundDelivery of acute stroke endovascular intervention can be challenging because it requires complex coordination of patient and staff across many different locations. In this proof-of-concept paper we (a) examine whether...

Dual-Satellite Alternate Switching Ranging/INS Integrated Navigation Algorithm for Broadband LEO Constellation Independent of Altimeter and Continuous Observation

In challenging environments such as forests, valleys and higher latitude areas, there are usually fewer than four visible satellites. For cases with only two visible satellites, we propose a dual-satellite alternate switching ranging integrated navigation algorithm based on the broadband low earth orbit (LEO) constellation, which integrates communication and navigation (ICN) technology. It is different from the traditional dual-satellite integrated navigation algorithm: the difference is that it can complete precise real-time navigation and positioning without an altimeter and continuous observation. First, we give the principle of our algorithm. Second, with the help of an unscented Kalman filter (UKF), we give the observation equation and state equation of our algorithm, and establish the mathematical model of multipath/non-line of sight (NLOS) and noise interference. Finally, based on the SpaceX constellation, for various scenarios, we analyze the performance of our algorithm through simulation. The results show that: our algorithm can effectively suppress the divergence of the inertial navigation system (INS), in the face of different multipath/NLOS interference and various noise environments it still keeps good robustness, and also has great advantages in various indicators compared with the traditional dual-satellite positioning algorithms and some existing 3-satellite advanced positioning algorithms. These results show that our algorithm can meet the real-time location service requirements in harsh and challenging environments, and provides a new navigation and positioning method when there are only two visible satellites.

Time-Driven Activity-Based Costing in Breast Cancer Care Delivery.

Accurate measurement of healthcare costs is required to assess and improve the value of oncology care. We aimed to determine the cost of breast cancer care provision across collaborating health care organizations. We used time-driven activity-based costing (TDABC) to calculate the complete cost of breast cancer care-initial treatment planning, chemotherapy, radiation therapy, surgical resection and reconstruction, and ancillary services (e.g., psychosocial oncology, physical therapy)-across multiple hospital sites. Data were collected between December 2019 and February 2020. TDABC steps involved (1) developing process maps for care delivery pathways; (2) determine capacity cost rates for staff, medical equipment, and hospital space; (3) measure the time required for each process step, both manually through clinic observation and using data from the Real-Time Location System (RTLS); and (4) calculate the total cost of care delivery. Surgical care costs ranged from $1431 for a lumpectomy to $12,129 for a mastectomy with prepectoral implant reconstruction. Radiation therapy was costed at $1224 for initial simulation and patient education, and $200 for each additional treatment. Base costs for chemotherapy delivery were $382 per visit, with additional costs driven by chemotherapy agent(s) administered. Personnel expenses were the greatest contributor to the cost of surgical care, except in mastectomy with implant reconstruction, where device costs equated to up to 60% of the cost of surgery. The cost of complete breast cancer care depended on (1) treatment protocols; (2) patient choice of reconstruction; and (3) the need for ancillary services (e.g., physical therapy). Understanding the actual costs and cost drivers of breast cancer care delivery may better inform resource utilization to lower the cost and improve thequality of care.

Development of a measurement setup to detect the level of physical activity and social distancing of ageing people in a social garden during COVID-19 pandemic

This study defines a methodology to measure physical activity (PA) in ageing people working in a social garden while maintaining social distancing (SD) during COVID-19 pandemic. A real-time location system (RTLS) with embedded inertial measurement unit (IMU) sensors is used for measuring PA and SD. The position of each person is tracked to assess their SD, finding that the RTLS/IMU can measure the time in which interpersonal distance is not kept with a maximum uncertainty of 1.54 min, which compared to the 15-min. limit suggested to reduce risk of transmission at less than 1.5 m, proves the feasibility of the measurement. The data collected by the accelerometers of the IMU sensors are filtered using discrete wavelet transform and used to measure the PA in ageing people with an uncertainty-based thresholding method. PA and SD time measurements were demonstrated exploiting the experimental test in a pilot case with real users.

Using a Real-Time Locating System to Evaluate the Impact of Telemedicine in an Emergency Department During COVID-19: Observational Study.

BackgroundTelemedicine has been deployed by health care systems in response to the COVID-19 pandemic to enable health care workers to provide remote care for both outpatients and inpatients. Although it is reasonable to suspect telemedicine visits limit unnecessary personal contact and thus decrease the risk of infection transmission, the impact of the use of such technology on clinician workflows in the emergency department is unknown.ObjectiveThis study aimed to use a real-time locating system (RTLS) to evaluate the impact of a new telemedicine platform, which permitted clinicians located outside patient rooms to interact with patients who were under isolation precautions in the emergency department, on in-person interaction between health care workers and patients.MethodsA pre-post analysis was conducted using a badge-based RTLS platform to collect movement data including entrances and duration of stay within patient rooms of the emergency department for nursing and physician staff. Movement data was captured between March 2, 2020, the date of the first patient screened for COVID-19 in the emergency department, and April 20, 2020. A new telemedicine platform was deployed on March 29, 2020. The number of entrances and duration of in-person interactions per patient encounter, adjusted for patient length of stay, were obtained for pre- and postimplementation phases and compared with t tests to determine statistical significance.ResultsThere were 15,741 RTLS events linked to 2662 encounters for patients screened for COVID-19. There was no significant change in the number of in-person interactions between the pre- and postimplementation phases for both nurses (5.7 vs 7.0 entrances per patient, P=.07) and physicians (1.3 vs 1.5 entrances per patient, P=.12). Total duration of in-person interactions did not change (56.4 vs 55.2 minutes per patient, P=.74) despite significant increases in telemedicine videoconference frequency (0.6 vs 1.3 videoconferences per patient, P<.001 for change in daily average) and duration (4.3 vs 12.3 minutes per patient, P<.001 for change in daily average).ConclusionsTelemedicine was rapidly adopted with the intent of minimizing pathogen exposure to health care workers during the COVID-19 pandemic, yet RTLS movement data did not reveal significant changes for in-person interactions between staff and patients under investigation for COVID-19 infection. Additional research is needed to better understand how telemedicine technology may be better incorporated into emergency departments to improve workflows for frontline health care clinicians.

Where do we find missing data in a commercial real-time location system? Evidence from 2 dairy farms

Real-time indoor positioning using ultra-wideband devices provides an opportunity for modern dairy farms to monitor the behavior of individual cows; however, missing data from these devices hinders reliable continuous monitoring and analysis of animal movement and social behavior. The objective of this study was to examine the data quality, in terms of missing data, in one commercially available ultra-wideband–based real-time location system for dairy cows. The focus was on detecting major obstacles, or sections, inside open freestall barns that resulted in increased levels of missing data. The study was conducted on 2 dairy farms with an existing commercial real-time location system. Position data were recorded for 6 full days from 69 cows on farm 1 and from 59 cows on farm 2. These data were used in subsequent analyses to determine the locations within the dairy barns where position data were missing for individual cows. The proportions of missing data were found to be evenly distributed within the 2 barns after fitting a linear mixed model with spatial smoothing to logit-transformed proportions (mean = 18% vs. 4% missing data for farm 1 and farm 2, respectively), with the exception of larger proportions of missing data along one of the walls on both farms. On farm 1, the variation between individual tags was large (range: 9–49%) compared with farm 2 (range: 12–38%). This greater individual variation of proportions of missing data indicates a potential problem with the individual tag, such as a battery malfunction or tag placement issue. Further research is needed to guide researchers in identifying problems relating to data capture problems in real-time monitoring systems on dairy farms. This is especially important when undertaking detailed analyses of animal movement and social interactions between animals.

Real-time localisation system for GPS-denied open areas using smart street furniture

Wifi-based localisation systems have gained significant interest with many researchers proposing different localisation techniques using publicly available datasets. However, these datasets are limited because they only contain Wifi fingerprints collected and labelled by users, and they are restricted to indoor locations.We have generated the first Wifi-based localisation datasets for a GPS-denied open area. We selected a busy open area at Murdoch University to generate the datasets using so-called “smart bins”, which are rubbish bins that we enabled to work as access points. The data gathered consists of two different datasets. In the first, four users generated labelled WiFi fingerprints for all available Reference Points using four different smartphones. The second dataset includes 2450865 auto-generated rows received from more than 1000 devices.We have developed a light-weight algorithm to label the second dataset from the first and we proposed a localisation approach that converts the second dataset from asynchronous format to synchronous, applies feature engineering and a deep learning classifier. Finally, we have demonstrated via simulations that by using this approach we achieve higher prediction accuracy, with up to 19% average improvement, compared with using only the fingerprint dataset.

The Case for Medical Device Cybersecurity Hygiene Practices for Frontline Personnel

The Case for Medical Device Cybersecurity Hygiene Practices for Frontline Personnel