Real-time Location System Research Articles

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.

Towards accurate and automatic emergency department workflow characterization using a real-time locating system

ABSTRACT This paper presents how patient throughput within an Emergency Department (ED) can be accurately and automatically characterized using a combination of data derived from a real-time location system (RTLS) and other traditional hospital IT systems such as Electronic Medical Records (EMR) and Laboratory Information Systems. Such insights can be used by a hospital to identify bottlenecks or inefficiencies and develop strategies to optimize and monitor patient flows. A descriptive, retrospective study was conducted among 1149 patients. Five KPIs, including time from arrival to triageand total length of stay, were used to evaluate ED timestamps to characterize the flow of the patient. A description of the techniques used to combine the various data sources to perform the accurate measurements is provided. The paper also describes the measurements obtained and indicates how real-time locating systems can contribute towards improving the quality of the timestamps generated compared to only using data from traditional hospital IT systems. A principial finding is that there is a large gap between the length of stay using only EMR data and the one computed combining EMR and RTLS data. Finally, the paper provides guidelines on how to deploy such a system effectively.

Total Cost of Ownership of Real-Time Locating System (RTLS) Technologies in Factories

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.

Real Time Locating Systems (RTLS) – An Enabling Technology to Support Engineering Education within Learning Factories

Real Time Locating Systems (RTLS) – An Enabling Technology to Support Engineering Education within Learning Factories

Retracted: Key Technologies of Real-Time Location Service in Satellite Navigation and Positioning Network Based on Internet of Things.

[This retracts the article DOI: 10.1155/2022/5191871.].

Antenna Delay-Independent Simultaneous Ranging for UWB-Based RTLSs

The ultra-wideband (UWB)-based real-time localization system (RTLS) is a promising technology for locating and tracking assets and personnel in real-time within a defined indoor environment since it provides high-ranging accuracy. However, its performance can be affected by the underlying antenna delays of UWB nodes, which act as a source of error during range estimations. Usually, measurement of the antenna delays is performed separately as a dedicated standalone procedure. Such an additional measurement procedure makes the UWB-based RTLS more tedious with manual interventions. Moreover, the air-time occupancy during the transmission and reception of signaling messages for range estimations between UWB node pairs also limits the serviceable capability of these networks. In this regard, we present a novel simultaneous ranging scheme that requires limited air-time occupancy during range estimations between UWB node pairs and also compensates for the error from the antenna delays. This paper provides a detailed mathematical modeling, system design, and implementation procedure of the proposed scheme. The effectiveness of the proposed scheme for locating a mobile node in an indoor environment is validated through experimental analysis. The results show that, compared to the state-of-the-art two-way ranging (TWR) method, the proposed scheme eliminates the requirement of dedicated standalone antenna delay measurement procedures of the nodes, increases air efficiency through the provision of simultaneous ranging, and provides relative root-mean-square errors (RMSEs) improvement for range and position estimations of approximately 54.52% and 39.96%, respectively.

Monitoring Worker Exposure to COVID-19 and Other Occupational Risks Using BLE Beacons

The COVID-19 pandemic has become a public health priority during 2020. Social safety distance is one of the most effective strategies to stop the spreading of the virus, as it reduces the dose of infectious particles that a person can receive. Real-time location systems (RTLS) based on ultrawideband (UWB), radio frequency identification (RFID), Global Position System (GPS), or Bluetooth Low Energy (BLE) can help keep workers safe at the workplace. The aim of the current paper is to develop a dosimeter proposal to monitor and control the distance and exposure time between workers based on BLE beacon technology considering viral load. Our proposal is based on a set of BLE beacons and safety distance estimation by filtering RSSI measurements with a Gaussian extended Kalman filter. According to the estimated proximity values and the exposure time, a finite state machine will alarm when the worker receives the maximum dose defined by health authorities. The proposed system can be applied to prevent any risk that can be eliminated or reduced controlling distances and/or exposition time of the worker to the occupational risk. The proposal is robust, is inexpensive, and respects the privacy of workers, and its accuracy is higher than that of existing smartphone applications. In future pandemic situations, the system can be easily updated to the safety distance and viral particle dose related with the new risk agent. The system can protect from additional risk incorporating beacons on the extra risk identified such as thermal, noise, or radiation.

Use of real time localization systems (RTLS) in the automotive production and the prospects of 5G – A literature review

ABSTRACT Numerous challenges in automotive production lead to an increased need for transparency and optimization. Real-Time-Location-Systems (RTLS) is a key tool for achieving this goal. They enable intelligent and automated production processes. Existing solutions such as Ultra-Wideband, Bluetooth-Low-Energy, or Radio-Frequency-Identification have drawbacks in costs, range, or accuracy. 5G is a newly developing standard, recently including high-accuracy positioning. It is unclear, however, if 5G positioning has reached industrial maturity. This contribution aims to determine the state-of-the-art of 5G positioning by performing a systematic literature review and comparing its findings to industrial positioning requirements. 143 articles were analyzed and categorized as: the fundamentals of radio-frequency positioning, an overview of existing solutions, the state-of-the-art, and the maturity of 5G as an industrial positioning system. Results show that, theoretically, centimeter-level accuracies are pursued. However, practical tests are rarely conducted. Concluding, 5G positioning shows great potential, but industrial pilots are required to validate the theoretical characteristics.

Accurate real-time SLAM based on two-step registration and multimodal loop detection

To improve the accuracy and efficiency of 3D LiDAR mapping, this paper improves the traditional point cloud registration and loop-detection methods and proposes a new scheme for accurate and real-time simultaneous localization and mapping systems. Cluster constraints are introduced into the front-end point cloud registration, and a two-step point cloud registration algorithm combining normal distribution transform and iterative closest point is proposed to speed up the point cloud registration. The effectiveness of this registration algorithm is fully validated in three sets of point cloud registration experiments. A loop detection process based on a height global descriptor for multimodal fusion is designed at the back end. The point cloud is encoded by this descriptor and fused with camera image information to generate a 1D operator to improve the search efficiency of loop closure frames. The proposed method is extensively evaluated on the KITTI data set and tested in playground periphery, fountain and parking lot environments. The results show that the accuracy of the proposed method outperforms the state-of-the-art LOAM and LeGO-LOAM in all three different scenarios.

Real-time location systems technology in the care of older adults with cognitive impairment living in residential care: A scoping review.

There has been growing interest in using real-time location systems (RTLS) in residential care settings. This technology has clinical applications for locating residents within a care unit and as a nurse call system, and can also be used to gather information about movement, location, and activity over time. RTLS thus provides health data to track markers of health and wellbeing and augment healthcare decisions. To date, no reviews have examined the potential use of RTLS data in caring for older adults with cognitive impairment living in a residential care setting. This scoping review aims to explore the use of data from real-time locating systems (RTLS) technology to inform clinical measures and augment healthcare decision-making in the care of older adults with cognitive impairment who live in residential care settings. Embase (Ovid), CINAHL (EBSCO), APA PsycINFO (Ovid) and IEEE Xplore databases were searched for published English-language articles that reported the results of studies that investigated RTLS technologies in persons aged 50 years or older with cognitive impairment who were living in a residential care setting. Included studies were summarized, compared and synthesized according to the study outcomes. A total of 27 studies were included. RTLS data were used to assess activity levels, characterization of wandering, cognition, social interaction, and to monitor a resident's health and wellbeing. These RTLS-based measures were not consistently validated against clinical measurements or clinically important outcomes, and no studies have examined their effectiveness or impact on decision-making. This scoping review describes how data from RTLS technology has been used to support clinical care of older adults with dementia. Research efforts have progressed from using the data to track activity levels to, most recently, using the data to inform clinical decision-making and as a predictor of delirium. Future studies are needed to validate RTLS-based health indices and examine how these indices can be used to inform decision-making.

Real-time Coordinate Estimation for Self-Localization of the Humanoid Robot Soccer BarelangFC

In implementation, of the humanoid robot soccer consists of more than three robots when played soccer on the field. All the robots needed to be played the soccer as human done such as seeking, chasing, dribbling and kicking the ball. To do all of these commands, it is required a real-time localization system so that each robot will understand not only the robot position itself but also the other robots and even the object on the field’s environment. However, in real-time implementation and due to the limited ability of the robot computation, it is necessary to determine a method which has fast computation and able to save much memory. Therefore, in this paper we presented a real-time localization implementation method using the odometry and Monte Carlo Localization (MCL) method. In order to verify the performance of this method, some experiment has been carried out in real-time application. From the experimental result, the proposed method able to estimate the coordinate of each robot position in X and Y position on the field.

Feasibility and Initial Results of a Daily Wearable Patient-Tracking Device for Optimization of Radiation Machine Utilization and Timely Treatment Delivery

<h3>Purpose/Objective(s)</h3> Several variables result in patient treatment delays in day-to-day radiotherapy operations that may cause patient dissatisfaction, inefficient machine utilization, and ad-hoc scheduling practices. Such challenges are magnified in larger centers offering multi-technology treatment platforms. Conventional approaches to manage machine times by examining beam-on time, or tracking the number of patients treated per day on each unit often, fail to provide a realistic picture for departmental capacity and staffing. As a result, we initiated a wearable tracking device project to better evaluate and document total time spent by each patient at each treatment unit for every fraction. <h3>Materials/Methods</h3> In 2022, a patient-specific, Real-Time Location System (RTLS) wearable device project was implemented to examine patient throughput, flows and delays within a single institution. The RTLS device is a small, clip-on location transponder provided to every patient at check-in for each visit. The total treatment time (TTT) required for the completion of each fraction was obtained by subtracting vault entry times (Ventry) from vault exit times (Vexit) as recorded by RTLS transponder sensors at the entrance of each vault. These times were then compared to scheduled Ventry, Vexit, and TTT for each fraction to examine variances. <h3>Results</h3> During a 3-week period dedicated to testing feasibility, a total of 2,298 fractions were delivered using 7 photon and 3 proton external beam radiation units. RTLS tracking data was successfully obtained for 678 fractions (30% of total fractions). Overall, 63.8% of tracked fractions started more than 5 min after their scheduled time and 31.2% of tracked fractions were completed after their scheduled allotted time. Median differences between scheduled and actual times for all machines were -10.1 min (-17.0 to 6.8 min), -6.6 min (-32.2 to 5.8 min), and 5.0 min (-19.0 to 8.0 min) for Ventry, Vexit and TTT, respectively. When comparing photon versus proton units, photon patients experienced longer delays with vault entry times (median: -13.0 vs -8.0 min). <h3>Conclusion</h3> Initial data support feasibility with 1/3 of all patients successfully tracked using RTLS within only 3 weeks of its implementation. The acquired baseline data demonstrate considerable variance between scheduled and actual times for radiation delivery, providing early insight for opportunities to improve efficiency and treatment timeliness. Future efforts will focus on methods to increase RTLS usage to over 90% through patient and staff education. The next phase of RTLS implementation will also examine the root causes of delayed fractions for schedule optimization and capacity modelling.

The Potential Role of an Adjunctive Real-Time Locating System in Preventing Secondary Transmission of SARS-CoV-2 in a Hospital Environment: Retrospective Case-Control Study

BackgroundThere has been an increasing demand for new technologies regarding infection control in hospital settings to reduce the burden of contact tracing.ObjectiveThis study aimed to compare the validity of a real-time locating system (RTLS) with that of the conventional contact tracing method for identifying high-risk contact cases associated with the secondary transmission of SARS-CoV-2.MethodsA retrospective case-control study involving in-hospital contact cases of confirmed COVID-19 patients, who were diagnosed from January 23 to March 25, 2022, was conducted at a university hospital in South Korea. Contact cases were identified using either the conventional method or the RTLS. The primary endpoint of this study was secondary transmission of SARS-CoV-2 among contact cases. Univariate and multivariable logistic regression analysis comparing test positive and versus negative contact cases were performed.ResultsOverall, 509 and 653 cases were confirmed by the conventional method and the RTLS, respectively. Only 74 contact cases were identified by both methods, which could be attributed to the limitations of each method. Sensitivity was higher for the RTLS tracing method (653/1088, 60.0%) than the conventional tracing method (509/1088, 46.8%) considering all contact cases identified by both methods. The secondary transmission rate in the RTLS model was 8.1%, while that in the conventional model was 5.3%. The multivariable logistic regression model revealed that the RTLS was more capable of detecting secondary transmission than the conventional method (adjusted odds ratio 6.15, 95% CI 1.92-28.69; P=.007).ConclusionsThis study showed that the RTLS is beneficial when used as an adjunctive approach to the conventional method for contact tracing associated with secondary transmission. However, the RTLS cannot completely replace traditional contact tracing.

Contact tracing using real-time location system (RTLS): a simulation exercise in a tertiary hospital in Singapore

ObjectiveWe aim to assess the effectiveness of contact tracing using real-time location system (RTLS) compared with the conventional (electronic medical records (EMRs)) method via an emerging infectious disease (EID) outbreak...

HealthStack: Providing an IoT Middleware for Malleable QoS Service Stacking for Hospital 4.0 Operating Rooms

Healthcare 4.0 is a new concept that originates from the evolution of hospitals due to technological advances in medical activities. Nowadays, more and more doctors and healthcare administrators require real-time data analysis obtained from sensors and surgery monitoring. Using real-time information could make the difference between death and life in such settings. Therefore, Quality of Service (QoS) is essential in this context because, without it, the results of the applications become unreliable. Given the background, this article proposes HealthStack, a sensor middleware model for operating room facilities. HealthStack aims at improving delay and jitter from applications and, at the same time, reducing resource consumption. Our scientific contributions are twofold: 1) a middleware for operating rooms with automatic QoS support for real-time data transmission and 2) a QoS strategy based on artificial neurons to select middleware components with critical performance. We developed a prototype that uses depth cameras and ultrawideband (UWB) real-time location systems (RTLSs) to monitor workflow during surgery. The evaluation demonstrates that the strategy improves the average jitter experienced by application by 92.3%. The results also reveal a reduction of network and CPU consumption by up to 61.8% and 8.3%.

Performance-Oriented UWB RTLS Decision-Making Approach

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.

A High-Precision and Low-Cost Broadband LEO 3-Satellite Alternate Switching Ranging/INS Integrated Navigation and Positioning Algorithm

To solve the problem of location services in harsh environments, we propose an integrated navigation algorithm based on broadband low-earth-orbit (LEO) satellite communication and navigation integration with 3-satellite alternate switch ranging. First, we describe the algorithm principle and processing flow in detail; next, we analyze and model the ranging error source and propose a combined multipath and non-line-of-sight (NLOS) error analysis model, which avoids discussing the complex multipath number of paths and its modeling process; in addition, we also propose a multimodal Gaussian noise-based interference model and analyze and model the LEO satellite orbital disturbance. The final simulation results show that our proposed algorithm can not only effectively overcome inertial navigation system (INS) divergence, but also achieve high positioning accuracy, especially when continuous ranging values are used. It can still ensure good anti-interference performance and robustness in terms of path and noise interference and by alternately switching ranging, there are other potential advantages. Compared to some of the existing representative advanced algorithms, it has higher accuracy, stronger stability and lower cost. Furthermore, it can be used as a location reference solution for real-time location services and life search and rescue in harsh environments with incomplete visual satellites and can also be used as a technical reference design solution for the future integration of communication and navigation (ICN).

Confidence interval estimation for fingerprint-based indoor localization

Fingerprint-based localization methods provide high accuracy location estimation, which use machine learning algorithms to recognize the statistical patterns of collected data. In these methods, the users’ locations can be estimated based on the received signal strength vectors from some transmitters. However, the data collection is a labor-intensive phase, and the collected data should be updated periodically. Many researchers have contributed to reducing this cost. The easiest way to remove the data collection cost is to use fingerprints generated by the model-based approaches, in which the trained machine learning algorithm can be updated based on the environment changes. Probabilistic-based localization algorithms, in addition to the user location, can estimate a region of interest called 2σ confidence interval in which the probability of user presence is 95%. Gaussian process regression (GPR) is a probabilistic method that can be used to achieve this goal. However, conventional GPR (CGPR) cannot accurately estimate the confidence interval when noise-free fingerprints generated by the model-based approaches are used in the training phase. In this paper, we propose a novel GPR-based localization algorithm, named enhanced GPR (EGPR), which improves the accuracy level of confidence interval estimation compared to the existing methods while fixing the level of computational complexity in the online phase. We also theoretically prove that GPR-based algorithms are minimum variance unbiased and efficient estimators. Experiments under line-of-sight and non-line-of-sight conditions demonstrate the superiority of our proposed method over counterparts in terms of accuracy as well as applicability in real-time localization systems.

RSSI-based hybrid algorithm for real-time tracking in underground mining by using RFID technology

Knowing the precise and real-time location of underground mining workers is essential for their health and safety in any emergency. However, the standard Global Positioning System (GPS) is insufficient for such indoor environments as it requires new infrastructure based on different technologies and algorithms. Instead, Radio Frequency Identification (RFID)-based real-time indoor localization systems and a hybrid algorithm are developed. The received-signal-strength (RSS) based positioning techniques are investigated and applied in indoor environments. A unique hybrid approach based on fingerprinting is proposed and developed to solve the disadvantages of the existing techniques. Consequently, the accuracy of this one-of-a-kind algorithm is found to be 2.52 m in an office and 3.13 m in an underground mine. We also compared the proposed hybrid algorithm to the Weighted K-Nearest Neighbor (WKNN). WKNN, on the other hand, has an accuracy of 4.01 m in the office and 4.33 m in underground mining environments.

Key Technologies of Real-Time Location Service in Satellite Navigation and Positioning Network Based on Internet of Things.

In this day and age, the necessities for route and situating exactness are getting ever more elevated. The global positioning and navigation system (GPS) can give high-accuracy and long haul route and situating data. But it largely depends on the external environment and is susceptible to environmental disturbances. As a result, the number of visible stars is insufficient, and even placement fails. The research on node positioning technology is of great significance to the research of wireless sensor networks, and node positioning technology is one of the important technologies in wireless sensor networks. Therefore, this paper will introduce the relevant algorithms and technologies of positioning in detail. The purpose of this text is to research how to analyze and research based on Internet of things (IoT) satellite navigation and positioning technology. And the wireless sensor network is described. The two simulation results have showed that, with the positioning technology proposed in this paper, the average positioning error of the anchor node can be kept a small constant regardless of the conditions of different packet sending intervals, changing moving rates, or increasing the transmission power and changing distance. The average positioning error provided in this paper has been kept at about 0.80 m, and the positioning accuracy is high, which is naturally newer and better than the Ssu positioning technology.