Real-time Location System Research Articles

COMPARATIVE ANALYSIS OF REAL-TIME LOAD TRACKING TECHNOLOGIES

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.

38 Application of Real-Time Location Systems for Automated Behavioral Monitoring in Sheep

Abstract Evaluating how, when, and where an animal moves in their environment can provide insights into their health and welfare states. Spatial tracking systems for monitoring sheep are less well developed than accelerometer-based systems, but have the potential to add important behavioral information to Precision Livestock Farming (PLF) applications. Global Positioning Systems (GPS) can be used to track pasture-based animals, but are not suitable to establish indoor locations. Real-Time Location Systems (RTLS) are a recent development that use radio-frequency signals emitted by tags to track the indoor location of an animal online and continuously. Raw RTLS data in the form of x, y coordinates can be used to calculate multiple spatial metrics, including velocity, acceleration, distance moved, the proportion of time an animal spends in different functional areas, social network attributes, and range size. RTLS can also be integrated with accelerometers to potentially improve predictive accuracy of behavioral algorithms. RTLS have been primarily tested and validated for indoor tracking of dairy cattle and have been used to assess behavioral time budgets and to detect space-use changes related to estrus or health status. For on-farm applications, these data must be transformed into threshold-based algorithms to generate notifications on changes in the health or welfare status of an animal. Algorithm development needs to account for confounding factors such as breed, sex, age, parity, and stage of lactation, as well as environmental variability that can influence the performance of decision-making tools under real-life conditions. In addition, independent validation studies of commercial systems are lacking, and many calculate positioning error with stationary objects rather than moving animals, potentially inflating accuracy estimates. In conclusion, there is growing empirical support for the use of RTLS as a PLF technology for on-farm animal health and welfare assessment. However, research is needed to validate these systems in sheep and identify spatial metrics that are accurate and robust predictors of health and welfare states for commercial applications.

Consuming patients’ days: Time spent on ambulatory visits by persons with cancer.

324 Background: Health care-related time burdens faced by persons with cancer can be substantial. In qualitative work, patients report that ‘’seemingly short clinic visits (e.g., a supposed 10-minute blood draw) often turn into all-day affairs.” We sought to estimate the total time spent (home-to-home) by patients with cancer on ambulatory services at an urban cancer center. Methods: We conducted a retrospective study of all patients with cancer scheduled for any ambulatory care (e.g., laboratory testing, imaging, procedures, infusions, clinician visits) at a Midwestern academic cancer center during a randomly selected week (Monday-Friday) in January 2023. We extracted sociodemographics, clinical characteristics, and services received from the electronic medical record. The primary exposure was the ambulatory care type or combination received by a patient on a day (e.g., clinician visit only, labs and infusion, etc.). Using data from the Real-Time Location System (RTLS) badge that patients wear from clinic entry to exit (standard of care to optimize clinic workflow), we tracked time spent in each patient location (e.g., exam room) and in the clinic overall. We estimated round-trip travel times using home and clinic zip codes and SAS/Google Maps. We calculated median parking time by directly observing 20 random patients between the clinic and their vehicles (e.g., parking ramp or valet). We calculated and summarized clinic and total (clinic + travel + parking) times for different ambulatory care types. Results: We analyzed 468 encounters by 436 unique patients (median age, 64 years, 52% women, 82% white race, 19% breast cancer). Median (IQR) clinic time per encounter was 118 (76-200) minutes. The median (IQR) round-trip driving distance and travel time was 33 (21-53) miles and 50 (36-68) minutes. The median parking time was 8 (6-10) minutes. The median (IQR) total time was 189 (136-277) minutes. Table 1 presents the times by type(s) of ambulatory services. Conclusions: In this single-center retrospective study, pursuing ambulatory cancer care on a given day required patients (and their accompanying care partners) to commit several hours to their care. These findings highlight the need to decrease care time demands on patients to mitigate time toxicity. Accounting for opportunity time costs and the coordination of other daily activities around ambulatory care, these results support our previously proposed practical measure of the time burdens of cancer care—that any day with in-person healthcare contact may represent a ‘’lost day.”[Table: see text]

Fusion localization for indoor airplane inspection using visual inertial odometry and ultrasonic RTLS

In this paper, the fusion localization system for the visual inertial odometry (VIO) and ultrasonic real-time localization system (RTLS) for indoor airplane inspection using drones is proposed. In a hangar environment, either trilateration-based RTLS or vision-based localization shows disadvantages and neither can be used alone. In this research, we design a configuration of VIO suitable for hangar environment and outlier filter on ultrasonic RTLS for non-line of sight situations, so that both can be fused using graph optimization. The proposed solution can provide more accurate localization than the visual odometry-only system as well as continue estimating positions in the absence of RTLS data. Localization and real-time performance of the proposed algorithm are evaluated through experimentation in a hangar and a flight test in an outdoor space.

New insight into social relationships in dairy cows and how time of birth, parity, and relatedness affect spatial interactions later in life

Social interactions between cows play a fundamental role in the daily activities of dairy cattle. Real-time location systems provide on a continuous and automated basis information about the position of individual cows inside barns, offering a valuable opportunity to monitor dyadic social contacts. Understanding dyadic social interactions could be applied to enhance the stability of the social structure promoting animal welfare and to model disease transmission in dairy cattle. This study aimed to identify the impact of different cow characteristics on the likelihood of the formation and persistence of social contacts in dairy cattle. The individual position of the lactating cows was automatically collected once per second for 2 weeks, using an ultra-wideband system on a Swedish commercial farm consisting of nearly 200 dairy cows inside a free-stall barn. Social networks were constructed using the position data of 149 cows with available information on all characteristics during the study period. Social contacts were considered as a binary variable indicating whether a cow pair was within 2.5 m of each other for at least 10 min per day. The role of cow characteristics in social networks was studied by applying separable temporal exponential random graph models. Our results revealed that cows of the same parity interacted more consistently, as well as those born within 7 d of each other or are closely related by pedigree. The repeatability of the topological parameters indicated a consistent short-term stability of the individual animal roles within the social network structure. Additional research is required to elucidate the underlying mechanisms governing the long-term evolution of social contacts among dairy cattle and to investigate the relationship between these networks and the transmission of diseases in the dairy cattle population.

Walking path images from real-time location data predict degree of cognitive impairment

BackgroundWe propose a novel approach that uses spatial walking patterns produced by real-time location systems to classify the severity of cognitive impairment (CI) among residents of a memory care unit. MethodsEach participant was classified as “No-CI”, “Mild-Moderate CI” or “Severe CI” based on their Mini-Mental State Examination scores. The location data was distributed into windows of various durations (5, 10, 15 and 30 min) and transformed into images used to train a custom convolutional neural network (CNN) at each window size. Class Activation Mapping was applied to the top-performing models to determine the features of images associated with each class. ResultsThe best performing model achieved an accuracy of 87.38 % (30-min window length) with an overall pattern that larger window sizes perform better. The class activation maps were effectively consolidated into a Cognitive Impairment Classification Value (CICV) score that distinguishes between No-CI, Mild-Moderate CI, and Severe CI. ConclusionThe class activation maps show that the CNN made relevant and intuitive distinctions for paths corresponding to each class. Future work should validate the proposed techniques with participants who are well-characterized clinically, over larger and diversified settings, and towards classification of neuropsychiatric symptoms such as motor agitation, mood, or apathy.

Harnessing a real-time location system for contact tracing in a busy emergency department

With the persistent threat of emerging infectious diseases (EID), digital contact tracing (CT) tools can augment conventional CT for the prevention of healthcare-associated infectious disease transmissions. However, their performance has yet to be comprehensively evaluated in the fast-paced emergency department (ED). We compared the CT performance of the radiofrequency identification (RFID) based real time location system (RTLS) with conventional Electronic Medical Records (EMR review), against continuous direct observations of close contacts ("gold-standard") in a busy ED during pandemic period. The cross-sectional study was conducted at the ED in a large tertiary-care hospital in Singapore, from December-2020 to April-2021. We computed the CT performance (sensitivity, specificity, PPV, NPV, kappa) of RTLS, EMR and combination of the 2 approaches (Hybrid-CT), with respect to the direct observations. Finally, we calculated the Mean Absolute Error (MAE) between the duration of each contact episode found via RTLS and direct observations. Both RTLS and the hybrid-CT approach had the highest sensitivity of 0.955 (vs EMR 0.455) and highest NPV of 0.997 (vs EMR 0.968). RTLS also had the highest PPV of 0.777 (vs EMR 0.714; vs hybrid-CT 0.712). RTLS had the strongest agreement with the direct observation (kappa= 0.848). MAE between contact durations of 80 direct observations and their respective RTLS contact time was 1.81 minutes. RTLS was validated to be a high-performing CT tool, with significantly higher sensitivity than conventional CT via EMR review. RTLS can be used with confidence in time-strapped EDs for time-sensitive CT for the prevention of healthcare-associated transmission of EIDs.

Low-Cost Real-Time Locating System Solution Development and Implementation in Manufacturing Industry

The present work originates from a previous study in which a low-cost Real-Time Locating System (RTLS) based on Ultra-Wideband signals was developed and tested both in a laboratory and in a real industrial environment for assessing its performance and determining the best configuration, according to some selected KPIs. Starting from the future research directions depicted, the evolution herein presented is twofold. First, tests performed in the laboratory are refined and deepened in terms of (i) different anchors’ arrangements and orientation; (ii) the increased number of tested tags; and (iii) the tags’ battery capacity test. Second, the development and deployment of the industrial solution as well is improved by means of a case for hosting tags to be positioned on the asset to be tracked, realized through 3D printing, in line with the industrial context requirements. Finally, an economic analysis is performed so as to demonstrate the convenience of the investment and the feasibility of the solution. Results are positive and promising in terms of both economic sustainability and implementation of the system in a real industrial environment and may constitute guidelines for practitioners and managers.

Contact tracing using a real-time location system in a tertiary-care hospital in Singapore

Background: Densely populated metropolitan cities like Singapore are susceptible to emerging infectious disease (EID) outbreaks. Singapore’s pandemic control measures include running biennial simulation exercises for all public hospitals on EID case management, in which a key assessment criterion is contact tracing. Current methods of contact tracing that involve retrospective review of the electronic medical record (EMR) are time-consuming and heavily manpower dependent, and they fail to capture a significant number of contacts. A real-time location system (RLTS) was accurate and effective in contact tracing. We compared the time taken to perform contact tracing and list of contacts identified for RTLS versus EMR, and we compared manpower and manpower hours required to perform contact tracing for RTLS versus EMR. Then we extrapolated the cost incurred by RTLS versus EMR. Methods: A prospective case study was conducted during a simulation exercise to determine and compare the list of contacts, time required, manpower required, and manpower hours required between RTLS and EMR. The costs of both methods were also compared. Results: RTLS identified almost 3 times more contacts than EMR (Fig. 2) with a 96.2% reduction in time taken, a 97.6% reduction in manpower, and a 97.5% reduction in manpower hours (Fig. 1). RTLS incurred significant equipment cost and therefore might require many contact-tracing episodes before providing economic benefit (Fig. 3). However, its speed and accuracy provided during contact tracing will allow the hospital to quickly isolate potentially exposed contacts, reducing the number of infected people during the spread of an infectious disease, particularly one like COVID-19. Conclusions: Albeit costly, RTLS is effective at contact tracing. RTLS has the potential to be the gold standard in contact-tracing methods of the future, particularly considering the current pandemic.Disclosures: None

Optimization of the Hardware Layer for IoT Systems Using a Trust-Region Method With Adaptive Forward Finite Differences

Trust-region (TR) algorithms represent a popular class of local optimization methods. Owing to straightforward setup and low computational cost, TR routines based on linear models determined using forward finite differences (FD) are often utilized for performance tuning of microwave and antenna components incorporated within the Internet of Things systems. Despite usefulness for design of complex structures, performance of TR methods vastly depends on the quality of FD-based local models. The latter are normally identified from perturbations determined a priori using either rules-of-thumb, or as a result of manual tuning. In this work, a framework for automatic determination of FD steps and their adjustment between the TR algorithm iterations is proposed. The method involves numerical optimization of perturbations so as to equalize the objective function changes w.r.t. the center design to the desirable precision. To maintain acceptable cost, the FD-tuning procedure is executed using the same approximation model as the one exploited in the course of the structure optimization. The proposed framework has been tested on a total of twelve design problems. Furthermore, the presented method has been thoroughly validated against TR-algorithms with static, a priori selected perturbations. Numerical results indicate that the proposed framework provides up to 50% performance improvement (in terms of the optimized designs quality) compared to the state-of-the-art TR-based approaches. Usefulness of the proposed method for the real-world Internet of Things systems has been implicitly demonstrated through utilization of one of the optimized structures in a hardware layer of a real-time localization system.

Assessment of a UWB Real Time Location System for Dairy Cows' Monitoring.

In the field of precision livestock farming, many systems have been developed to identify the position of each cow of the herd individually in a specific environment. Challenges still exist in assessing the adequacy of the available systems to monitor individual animals in specific environments, and in the design of new systems. The main purpose of this research was to evaluate the performance of the SEWIO ultrawide-band (UWB) real time location system for the identification and localisation of cows during their activity in the barn through preliminary analyses in laboratory conditions. The objectives included the quantification of the errors performed by the system in laboratory conditions, and the assessment of the suitability of the system for real time monitoring of cows in dairy barns. The position of static and dynamic points was monitored in different experimental set-ups in the laboratory by the use of six anchors. Then, the errors related to a specific movement of the points were computed and statistical analyses were carried out. In detail, the one-way analysis of variance (ANOVA) was applied in order to assess the equality of the errors for each group of points in relation to their positions or typology, i.e., static or dynamic. In the post-hoc analysis, the errors were separated by Tukey's honestly significant difference at p > 0.05. The results of the research quantify the errors related to a specific movement (i.e., static and dynamic points) and the position of the points (i.e., central area, perimeter of the investigated area). Based on the results, specific information is provided for the installation of the SEWIO in dairy barns as well as the monitoring of the animal behaviour in the resting area and the feeding area of the breeding environment. The SEWIO system could be a valuable support for farmers in herd management and for researchers in the analysis of animal behavioural activities.

CHRONOS Project: The Transformation of Time-dependent Clinical Trajectories into Intelligent Ones Using an Innovative Technological Solution

Introduction:The health system faces many challenges including the lack of personnel or resources and the overcrowding of emergency rooms. In this context, Real Time Locating Systems (RTLS) offer the possibility of improving the efficiency, safety and quality of care management. Clinical trajectories are currently very dependent on manual processes. We believe that real-time management systems that use geolocation can optimize time-dependent clinical trajectories, improve critical care and transform the health network for patients, caregivers and managers. Typically, RTLS tools require a significant investment in terms of installation, configuration, and integration.Method:The Nano Data Center (NDC) system developed by Humanitas Solutions is equipped with an advanced and low-cost IT infrastructure. It is self-deploying, self-configurable and allows geolocation and autonomous telecommunication with multiple interfaces (WIFI, Bluetooth, electrical). It requires a power source and operates without requiring access to technological infrastructures, which is the major difference with similar products based mainly on cloud computing and dependent on internet connectivity. We tested, as a pilot project, the deployment of the NDC system in a complex hospital environment (Centre intégré de la santé et des services sociaux de la Montérégie-Centre, Quebec, Canada) in order to demonstrate its potential use.Results:Using the NDC system, we were successful in establishing an autonomous communication network over several hospital floors. This innovation made it possible to support the real-time geolocalization of fictive patients and the creation of a real-time dashboard for monitoring clinical trajectories, analyzing data, and evaluating performance.Conclusion:The next development phases of the CHRONOS project include real-time notification and transformation of clinical trajectories into smart trajectories. The independence of the NDC system in terms of infrastructures would allow its deployment in low-resource environments, such as temporary installations or remote areas. Thus, its potential benefit in creating connected environments in disaster situations.

Fusion of Vision Deep-Learning Person Detection and Radio Beacon Ranging for Identifying and Locating Factory Workers

Assessment of an individual factory worker's productivity and safety has been increasingly demanded in the manufacturing industry. Although the long-term accuracy of identifying and locating people are key for such applications, recent technologies such as vision-based person re-identification (Re-ID) and radio-based Real Time Location Systems (RTLS) do not meet the requirements in open-world settings. In addition, vision-based person Re-ID might cause privacy concerns as it utilizes a person's appearance for identification. This article explains a sensor fusion framework that combines vision deep-learning person detection and radio beacon ranging to match the requirements for open-world settings and preserves privacy through an opt-out option. Its scalability is evaluated via Rank-1 person identification accuracy with images generated by a three-dimensional (3D) game engine to conduct hard-to-reproduce extreme scenarios. The representative Rank-1 is 88.7% with 4 people for low-latency applications ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> personalized geofencing) and 90.8% with 8 people for latency-tolerant applications ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> individual worker's productivity analysis).

Order picking system evaluation using RTLS method

&#x0D; 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. he abstract contains a short, general description of the topic and the research shown in the paper.

Real-Time Location Systems for Quality Improvement: Promises, Challenges, and Recommendations.

Armstrong Institute for Patient Safety and Quality, Department of Anesthesiology and Critical Care Medicine, Institute for Clinical and Translational Research, and JHSOM Simulation Center, Johns Hopkins University School of Medicine, Baltimore, Maryland. Correspondence: Michael A. Rosen, PhD, Armstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, 750 E Pratt S, 15th Floor, Baltimore, MD 21202 ([email protected]). The author declares no conflicts of interest.

Estimation of Measurement Uncertainty of the Real-Time Location System (RTLS) with Ultra-Wideband (UWB) Technology

The need to control the real-time location of assets is increasingly relevant worldwide. The Ultra-wideband (UWB) technology is an IoT solution for real-time locating systems (RTLS). The location of the asset is obtained by the signal exchange between a wireless tag (asset) and fixed anchors. The tag interacts with the fixed anchors, defining its position through the distances obtained by trilateration. This data is sent to the server through the gateway. It is well-known that this process has several sources of errors. However, the measurement uncertainty assessment of UWB technology is an important topic regarding its scope of use. This paper presents a task-specific measurement uncertainty evaluation for the UWB positioning system, according to the ISO GUM. It aims to propose a method to support decision-making regarding the possible uses of UWB technology. The position provided by the UWB is compared with reference points using Cartesian coordinates that are measured with a total station, providing metrological reliability. Using the information from the estimated uncertainty, one can define the minimum tolerance interval associated with UWB technology for a given use. A case study demonstrates the method.

COVID-19 Pandemi Önlemleri Altında Çalışan Üretim Tesisleri için Gerçek

By reason of the COVID-19 pandemic, essential digital transformations are taking place in many areas of business life. Although the most important one of these transformations is due to the widespread use of the remote working model, the production sector does not have the opportunity to switch to such a model completely. Therefore, it is inevitable to maintain social distance to prevent the spread of COVID-19 while working in production facilities. In this study, a real-time location system (RTLS) model is proposed to keep track of social distance in production facilities and to ensure occupational health safety (OHS) at the same time. Since the social distance rule is essential for every production facility, the most important feature of the proposed system is that it can easily be integrated into the standard personnel tracking system in almost every enterprise. Besides, the proposed RTLS is designed as an efficient system based on ultra-wideband and radio-frequency identification, which can operate as a closed-loop monitoring system within itself. An adequately installed RTLS can monitor the position of employees in real-time and provides to intervene in the situation instantly when necessary. In case of a violation of social distance or a situation against OHS, it can be prevented instantly by the proposed system. It is also a useful model in the management of emergencies.

Real-Time Location System (RTLS) Based on the Bluetooth Technology for Internal Logistics

The problem of object localization in indoor environments is very important in order to make a company effective and to detect disruption in the logistics system in real-time. Present research investigates how the IoT (Internet of Things) location system based on Bluetooth can be implemented for this solution. The location based on the Bluetooth is hard to predict. Radio wave interference in this frequency is affected by other devices, steel, vessels containing water, and more. However, proper data processing and signal stabilization can increase the accuracy of the location. To be sure that the location system based on the BT (Bluetooth) can be implemented for real cases, an analysis of signal strength amplitude and disruption was made. The paper presents R&amp;D (Research and Development) works with a practical test in real cases. The signal strength fluctuation for the receiver is between 7 and 10 dBm for ESP32 device and between 13 and 14 dBm for Raspberry. For commercial implementation the number of devices scanned in the time window is also important. For Raspberry, the optimal time window is 5 s; in this time six transmitters can be detected. ESP32 has a problem with detecting devices in a short time, as just two transmitters can be detected in 4–8 s time window. Localisation precision depends on the distance between transmitter and receiver, and the angle from the axis of the directional antenna. For the distance of 10 m the measurement error is 1.2–6.1 m, whilst for the distance of 40 m the measurement error is 4.9 to 24.6 m. Using a Kalman filter can reduce the localization error to 1.5 m.

Implementation and Use of Real-Time Location Systems in Hospital Environments – Rapid Scoping Review of Human Factors Considerations

Real-Time Location Systems (RTLS) are rapidly being adopted in healthcare environments to monitor or track patients, workers, equipment, supplies and more, with numerous studies discussing the impact of this emerging technology. However, a more global view of such studies, those focused on human factors considerations in implementing RTLS is lacking. In response, we present preliminary findings from a rapid scoping review of factors related to implementing RTLS in healthcare environments, with a specific focus on impact to healthcare workers. We conducted keyword searches of databases such as CINAHL, EI Engineering Village, Scopus, IEEE, Web of Science, and several ProQuest journals between July and September 2022. The results were screened to identify results pertaining specifically to the experience of implementing RTLS in recent years. The extracted studies offer insight into the human factors that affect the implementation and use of this technology. Namely, the literature points to undesirable outcomes that occur when organizational efficiency is emphasized over providing demonstrable benefits to workers. Conversely, successful implementations are shown to feature increased worker involvement in the design process and increased communication and training following implementation. Further, the reviewed literature supports the involvement of human factors practitioners in future research activities investigating RTLS implementation and its impact on hospital infrastructure and operations.

Cow characteristics associated with the variation in number of contacts between dairy cows

In modern freestall barns where large groups of cows are housed together, the behavior displayed by herd mates can influence the welfare and production of other individuals. Therefore, understanding social interactions in groups of dairy cows is important to enhance herd management and optimize the outcomes of both animal health and welfare in the future. Many factors can affect the number of social contacts in a group. This study aimed to identify which characteristics of a cow are associated with the number of contacts it has with other group members in 2 different functional areas (feeding and resting area) to increase our understanding of the social behavior of dairy cows. Inside 2 herds housed in freestall barns with around 200 lactating cows each, cow positions were recorded with an ultra-wideband real-time location system collecting all cows' positions every second over 2 wk. Using the positioning data of the cows, we quantified the number of contacts between them, assuming that cows spending time in proximity to one another (within a distance of 2.5 m for at least 10 min per day) were interacting socially. We documented in which barn areas these interactions occurred and used linear mixed models to investigate if lactation stage, parity, breed, pregnancy status, estrus, udder health, and claw health affect the number of contacts. We found variation in the number of contacts a cow had between individuals in both functional areas. Cows in later lactation had more contacts in the feeding area than cows in early lactation. Furthermore, in one herd, higher parity cows had fewer contacts in the feeding area than first parity cows, and in the other herd, cows in third parity or higher had more contacts in the resting area. This study indicates that cow characteristics such as parity and days in milk are associated with the number of contacts a cow has daily to its herd mates and provides useful information for further research on social interactions of dairy cows.