Real-time Tracking Data Research Articles

Real-Time Tracking Data and Machine Learning Approaches for Mapping Pedestrian Walking Behavior: A Case Study at the University of Moratuwa.

The growing urban population and traffic congestion underline the importance of building pedestrian-friendly environments to encourage walking as a preferred mode of transportation. However, a major challenge remains, which is the absence of such pedestrian-friendly walking environments. Identifying locations and routes with high pedestrian concentration is critical for improving pedestrian-friendly walking environments. This paper presents a quantitative method to map pedestrian walking behavior by utilizing real-time data from mobile phone sensors, focusing on the University of Moratuwa, Sri Lanka, as a case study. This holistic method integrates new urban data, such as location-based service (LBS) positioning data, and data clustering with unsupervised machine learning techniques. This study focused on the following three criteria for quantifying walking behavior: walking speed, walking time, and walking direction inside the experimental research context. A novel signal processing method has been used to evaluate speed signals, resulting in the identification of 622 speed clusters using K-means clustering techniques during specific morning and evening hours. This project uses mobile GPS signals and machine learning algorithms to track and classify pedestrian walking activity in crucial sites and routes, potentially improving urban walking through mapping.

Inventory Management System

For organizations that handle transactions involving consumer goods, an inventory management system is critical for quality control. A huge retail store could run out of supply of a critical item if inventory is not properly managed. When it’s time to reorder, an effective inventory management system will notify the retailer. This inventory management system is also useful for tracking huge shipments automatically. Counting each pair of stocks by hand will almost certainly result in a mistake. The risk of human error can be reduced by using an automated inventory management system. An Inventory Management System also aids in the tracking of retail product theft, providing useful information regarding store revenues and the need for theft-prevention devices. Scanning a barcode on the item or a barcode scanner is how Automated Inventory Management Systems function. The central computer system then keeps track of this data. The purchase order can also include a list of items that need to be pulled for packaging and shipping. In this situation, the Inventory Management System can perform a range of tasks. It can assist a warehouse worker in locating things on an order list, encoding shipment information such as tracking numbers and delivery addresses and removing purchased items from the inventory tally to maintain a correct count of in-stock items. All of this information works together to give firms real-time inventory tracking data. The simple search in a database makes it easy to find and look at inventory information in real-time.The inventory management system project abstract tells the overall function of the software. It consists of the reason why the project was proposed and the solutions made to answer the needs of the targeted users. To enlighten you with this, here’s the Inventory Management System Project Abstract

Wildlife watch

The escalating biodiversity loss demands a paradigm shift in wildlife conservation. This paper proposes an innovative AI system for holistic wildlife management. The deep learning algorithms identify individual animals through biometrics in camera traps, drone footage, and bioacoustics. This surpasses traditional methods, enabling tracking across vast landscapes. The real-time animal tracking data, analyzed by machine learning, allows for early detection of poaching, habitat disturbances, and animal distress. Furthermore, the system integrates environmental sensors to provide a holistic understanding of ecological conditions. The correlating animal movement with environmental data helps identify crucial habitats and predict climate threats. This unified platform empowers proactive wildlife management, transitioning conservation from reactive to evidence-based practices for long-term biodiversity preservation.

Nutrition, frailty assessment, and interventions for the liver transplant candidate.

Nutrition, frailty assessment, and interventions for the liver transplant candidate.

Process Loss Reduction: Implementing Process Management System Through Digitization using a Web-Based Application

This research identifies problem in Ethiopian denim trouser manufacturing unit between cut to ship, resulting in material loss. The area of study is chosen from the cutting to the packing of the unit. The study investigates the various process losses and their causes. A web-based application that uses a QR code to track bundle movement is attached with bundles which will also generate production, Quality, Machine breakdown, recut, and WIP reports. The design and system developed can track Real-time material movement throughout the process and generate real-time insightful and actionable data. Using real-time tracking, planning, and insightful data provides a vision for this project. The significance of the research is immense as Reliance on the data is raised, planning becomes more manageable and effective, monitoring is improved, WIP is controlled, Gap Mitigation (Capacity to Performance) is streamlined and above all, "Transparency" of the floor becomes sharper.

Blockchain and Supply Chain Management: The Future of Trust and Transparency

Abstract: Supply chain management involves the coordination of various parties in the production, handling, and distribution of goods. Blockchain technology offers a new approach to managing the supply chain by enabling the creation of secure, decentralized, and transparent networks for tracking and verifying the movement of goods. This can help improve supply chain efficiency, reduce the risk of fraud and counterfeiting, and provide greater visibility and traceability throughout the entire supply chain. With its ability to facilitate real-time tracking, smart contracts, and secure data sharing, blockchain technology has the potential to revolutionize the way supply chains are managed.

Measuring nursing movements using real time tracking data at the Royal Wolverhampton Hospital Trust

BackgroundReal time location systems (RTLS) are increasingly used in healthcare with applications that include contract tracing and staffing. However, their potential to provide organizational insights requires staff compliance with the system. Materials and MethodsOur goal is to assess how many nurses are using the RTLS correctly (i.e. complying to the system). We collect RTLS data on the movements of nurses at the Royal Wolverhampton NHS Trust. We identify the number of RTLS active nurses and compare it to what expected from the nurses’ rotas. ResultsWe find that a significant number of nurses appear not to be active from the RTLS data. For approximately 15% of the active users, RTLS records below 10 movements per day. Nevertheless, most of the active users have daily RTLS times consistent with the average shift length. ConclusionApplications of RTLS data may need to account for imperfect compliance of staff to the system.

Development of AWS based E-invoice Platform for Trading

Abstract: Global container shipping is the phenomenon of packing goods into containers and transporting them across country borders. A global container shipping trip often involves multiple carriers, third party logistics firms, and fourth party logistics firms. Based on previously agreed-upon contract pricing with the shippers, these businesses bill base service costs, unexpected service fees, and value-added service fees through freight invoices. This study introduces an AWS-based system for creating electronic invoices for carriers of goods when one or more carriers are involved in the shipment of products from a shipper's origin location to a destination location outside of the country of origin. Real-time shipment tracking data and previously agreed-upon service contract pricing between the shipper and the carrier are largely used in the preparation of an invoice for a carrier. Our solution improves the effectiveness of the e-invoicing process and reduces expenses for the shippers and carriers involved in international trade. The' main reasons for adopting AWS-based e-invoicing solutions are to decrease the frequency of invoice disputes, speed up dispute settlement, and offer real-time audits

A machine learning approach to predict production time using real-time RFID data in industrialized building construction

Industrialized building construction is an approach that integrates manufacturing techniques into construction projects to achieve improved quality, shortened project duration, and enhanced schedule predictability. Time savings result from concurrently carrying out factory operations and site preparation activities. In an industrialized building construction factory, the accurate prediction of production cycle time is crucial to reap the advantage of improved schedule predictability leading to enhanced production planning and control. With the large amount of data being generated as part of the daily operations within such a factory, the present study proposes a machine learning approach to accurately estimate production time using (1) the physical characteristics of building components, (2) the real-time tracking data gathered using a radio frequency identification system, and (3) a set of engineered features constructed to capture the real-time loading conditions of the job shop. The results show a mean absolute percentage error and correlation coefficient of 11% and 0.80, respectively, between the actual and predicted values when using random forest models. The results confirm the significant effects of including shop utilization features in model training and suggest that predicting production time can be reasonably achieved.

Analysis of Change and Driving Factors of PM2.5 Mass Concentration in Tianjin from 2000 to 2020

Based on real-time tracking data, PM2.5 mass concentration, and meteorological observations of the Tianjin Meteorological Bureau and the Ecological Environment Bureau, combined with the fine particle meteorological condition diffusion index constructed using the environmental model, the change and driving factors of the PM2.5 mass concentration in Tianjin from 2000 to 2020 were studied to analyze the impact of meteorology on the atmospheric environment. The study showed that change in PM2.5 mass concentration in Tianjin took place in three stages from 2000 to 2020; the first stage showed a continuous increase from 2000 to 2007. The rapid increase in emissions in this stage was the dominant factor, and its effect was four times that of the annual fluctuation in meteorological conditions. The second stage was from 2007 to 2013, in which the PM2.5 mass concentration fluctuated, with two peak years (2007 and 2013). The emissions were stable in this stage. The annual fluctuation of meteorological conditions had an important influence on the annual fluctuation in PM2.5 mass concentration. The third stage was from 2013 to 2020; the PM2.5 mass concentration decreased rapidly, and the decline in emissions was decisive, which reduced the PM2.5 mass concentration by 40% to 50%. The improvement in the meteorological diffusion conditions also provided a positive contribution, which reduced the PM2.5 mass concentration by approximately 10%. Based on the analysis of the data over the past 20 years, the annual variation in atmospheric diffusion conditions caused by the annual variation in meteorological conditions was periodic, with trough values from 2003 to 2004 and 2013 to 2015 and peaks from 2008 to 2010 and 2018 to 2020; the distance between peaks and valleys was approximately 11 years. It was estimated that the next atmospheric diffusion condition valley stage will occur circa 2025. The average intensity of the annual fluctuation in atmospheric diffusion conditions caused by the annual variation in meteorological conditions was 4%, which can explain 25%-50% of the annual variation in PM2.5 mass concentration over the past 20 years, with a difference between peaks and valleys of 16%. The periodic fluctuations in meteorological diffusion conditions have an important impact on the future PM2.5 target setting and corresponding measures design.

P09.03 Fully integrating functional Ultrasound (fUS) into the onco-neurosurgical operating room: Towards a new real-time, high-resolution image-guided resection tool with multimodal potential

Abstract BACKGROUND Onco-neurosurgical practice still relies heavily on pre-operatively acquired images to guide intra-operative decision-making for safe tumor removal, a practice with inherent pitfalls such as registration inaccuracy due to brain shift, and lack of real-time (functional) feedback. Exploiting the opportunity for real-time imaging of the exposed brain can improve intra-operative decision-making, neurosurgical safety and patient outcomes. Previously, we described functional Ultrasound (fUS) as a high-resolution, depth-resolved imaging technique able to detect functional regions and vascular morphology during awake resections. Here, we present for the first time fUS as a fully integrated, MRI/CT-registered imaging modality in the OR. MATERIAL AND METHODS fUS relies on high-frame-rate (HFR) ultrasound, making the technique sensitive for very small motions caused by vascular dynamics (µDoppler) and allowing measurements of changes in cerebral blood volume (CBV) with micrometer-millisecond precision. This opens up the possibility to 1) detect functional response, as CBV-changes reflect changes in metabolism of activated neurons through neurovascular coupling and 2) visualize in-vivo vascular morphology of tumor and healthy tissue. During a range of anesthetized and awake onco-neurosurgical procedures we acquired images of brain and spinal cord using conventional linear ultrasound probes connected to an experimental acquisition unit. Building on Brainlab’s ‘Cranial Navigation’ and ‘Intra-Operative Ultrasound’ modules, we could co-register our intra-operative Power Doppler Images (PDIs) to patient-registered MRI/CT-data. Using the ‘IGTLink’ research interface, we could access and store real-time tracking data for informed volume reconstructions in post-processing. RESULTS Intra-operative fUS could be registered to MRI/CT-images in real-time, showing overlays of PDIs at imaging depths of >5 centimeters. During meningioma resections, these co-registered PDIs revealed fUS’ ability to visualize the tumor’s feeding vessels and surrounding healthy vasculature prior to durotomy, with a level of detail unprecedented by conventional MRI-sequences. Comparing post-operatively reconstructed 3D-vascular maps of pre- and post-durotomy acquisitions, further confirmed the dural dependency of the vascular network feeding the tumor. During awake resections, fUS revealed distinct functional areas as activated during motor and language tasks. CONCLUSION fUS is a new real-time, high-resolution and depth-resolved imaging technique, combining characteristics uniquely beneficial for a potential image-guided resection tool. The successful integration of fUS in the onco-neurosurgical OR demonstrated by our team, is an essential step towards clinical integration of fUS, as well as the technique’s validation against modalities such as MRI and CT.

Markerless Real-Time 3-Dimensional kV Tracking of Lung Tumors During Free Breathing Stereotactic Radiation Therapy

PurposeAccurate verification of tumor position during irradiation could reduce the probability of target miss. We investigated whether a commercial gantry-mounted 2-dimensional (2D) kilo-voltage (kV) imaging system could be used for real-time 3D tumor tracking during volumetric modulated arc therapy (VMAT) lung stereotactic body radiation therapy (SBRT). Markerless tumor tracking on kV fluoroscopic images was validated using a life-like moving thorax phantom and subsequently performed on kV images continuously acquired before and during free-breathing VMAT lung SBRT. Methods and MaterialsThe 3D-printed/molded phantom containing 3 lung tumors was moved in 3D in TrueBeam developer mode, using simulated regular/irregular breathing patterns. Planar kV images were acquired at 7 frames/s during 11 Gy/fraction 10 MV flattening filter free VMAT. 2D reference templates were created for each gantry angle using the planning 4D computed tomography inspiration phase. kV images and templates were matched using normalized cross correlation to determine 2D tumor position, and triangulation of 2D matched projections determined the third dimension. 3D target tracking performed on cone beam computed tomography projection data from 18 patients (20 tumors) and real-time online tracking data from 2 of the 18 patients who underwent free-breathing VMAT lung SBRT are presented. ResultsFor target 1 and 2 of the phantom (upper lung and middle/medial lung, mean density –130 Hounsfield units), 3D results within 2 mm of the known position were present in 92% and 96% of the kV projections, respectively. For target 3 (inferior lung, mean density –478 Hounsfield units) this dropped to 80%. Benchmarking against the respiratory signal, 13/20 (65%) tumors (10.5 ± 11.1 cm3) were considered successfully tracked on the cone beam computed tomography data. Tracking was less successful (≤50% of the time) in 7/20 (1.2 ± 1.5 cm3). Successful online tracking during lung SBRT was demonstrated. Conclusions3D markerless tumor tracking on a standard linear accelerator using template matching and triangulation of free-breathing kV fluoroscopic images was possible in 65% of small lung tumors. The smallest tumors were most challenging.

Evaluating the Need For An Analytical Model of Correlated mm-Wave Channels of 5G For Mobility-Related Scenarios

Communication with the millimeter-wave (mm-Wave) is one of the new features present in the fifth generation (5G) mobile networks. The possibility and challenges related to a large population have encouraged many study-based studies to evaluate proposed solutions. Communication in millimeter waves is one of the following Great innovations of the 5G mobile network. For a big reason: Available bandwidth value. However, a millimeter-wave channel given the nature of harsh distribution and sensitivity to congestion. Therefore, the correct modeling of mm-Wave channels is the basis for obtaining accurate results in the simulation of the mm-Wave mobile system. The quality of the mm-wave simulation depends on the channel model, but the favorite channel models of millimeter waves such as the spatial channel model (SCM) have advanced computer density and reduce the density of the solution. End-to-end, systematic development and research. This paper gives an informative exercise in the mm-Wave full-grown section included in ns-3 open source testing system. The module incorporates a variety of models as well as the ability to combine real-time measurements or radiation tracking data. This paper provides equal distribution of a few measurements, for example, SINR in very big cases. We also provide pieces of information on the use of cases where using an easy model can produce the official outcome.

Investigating Offshore Helicopter Pilots’ Cognitive Load and Physiological Responses during Simulated In-Flight Emergencies

ABSTRACT Objectives: This study was designed to explore pilots’ emergency response performance by collecting real-time physiological and cognitive workload data during pre-defined offshore helicopter scenarios in a flight simulator. Background: Qualification processes require helicopter pilots to complete scheduled simulation training to ensure competency in areas that would otherwise be too dangerous to practice while flying the actual helicopter. Unfortunately, little is known about how effective this simulation training is in regard to cognitive and physiological responses. Methods: Ten qualified pilots completed six flight simulations while real-time eye tracking and physiological data were collected. The pilots were assigned to one of two groups based on their regular flying position (First Officer (FO) or Captain). Results: The findings indicated that there is a significant difference in maximal Index of Cognitive Activity (ICAmax) and maximal heart rate (HRmax) values between the two groups while completing the same in-flight emergency scenarios. Conclusions: Results suggest that FOs found the sessions more cognitively demanding and also indicated they would benefit from learning how Captains conduct their radial scan of instruments. Therefore, it is recommended that visual search patterns are included in initial training, all flight simulator training includes eye tracking, heart rate data are collected, and that future longitudinal research follows new pilots through their training/upgrading process.

Abstract 26: A novel electronic platform to improve clinical trial workflow and screening

Abstract Background: Early-phase clinical trials are increasingly complex, with “seamless” phase I/II trial designs that include multiple parallel disease and/or biomarker-selected expansion cohorts. Challenges for participating sites in phase 1 (P1) trials include rapid identification of patients for available trial slots, high screen failure (SF) rates, and workload distribution among nurses and data coordinators. The Princess Margaret (PM) Cancer Centre Solid Tumor P1 program is the largest early-phase clinical trial program in Canada. There are currently 53 actively recruiting clinical trials, and approximately 250-300 patients are enrolled annually. To improve operational efficiency at the point of care, we designed a novel electronic platform, termed Phase One Spot Tracker (POST). Methods: An electronic, password-restricted, web-based tracker and smartphone-enabled app was created using PHP Laravel, JavaScript (iOS), and Java (Android). The intention was to replace the two previously used Excel spreadsheets, where one listed the trial information and the other included available slot allocations by trial. These spreadsheets were cumbersome to use in clinic, without the ability to search or filter. POST enabled all users to access the data from any computer or phone, increased the ease of updating information in real time, and functioned as a search engine to locate available spots more quickly. It contains specific information including brief trial description, key eligibility criteria, biopsy requirements, status of trial slots (e.g., screening, available, pending, etc.). The data security of POST is ensured by Amazon Web Services. Results: Prior to launching POST, three time-measured simulations showed that it reduced the coordinators’ workload to update trial information by 30 minutes. Currently POST is used by 65 users, including 7 physicians, 14 nurses, and 29 coordinators at the PM Cancer Centre. POST is used by investigators during a weekly P1 new patient consultation clinic to identify trial candidates as well as in weekly P1 team meetings to review all patients enrolled and approached for clinical trials. We are enhancing the POST platform to enable tracking of SF (patients who undergo study-specific screening procedures but are not enrolled in a clinical trial), timeline for replacing patients who screen fail, and reasons for SF. Conclusions: POST is an electronic, smart phone-enabled platform that can be implemented at the point of care for early-phase clinical trials. POST can also provide real-time tracking data about operational metrics (startup time, screening time, enrollment data, nursing and data coordinator workload, and screen failures) that can be used to drive quality improvement. POST can be extended to other disease site groups as well as to other institutions. This will eventually lead to an increase in work efficiency and provide a better quality of care for cancer patients. Citation Format: Ramy R. Saleh, Olivia Chan, Silvi Kuld, Patrick Marban, Anna Spreafico, Aaron Hansen, Albiruni Razak, Lillian L. Siu, Philippe L. Bedard. A novel electronic platform to improve clinical trial workflow and screening [abstract]. In: Proceedings of the AACR Special Conference on Advancing Precision Medicine Drug Development: Incorporation of Real-World Data and Other Novel Strategies; Jan 9-12, 2020; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_1):Abstract nr 26.

Impact of satellite linked radio transmitting (SLRT) tags on the dorsal fin of subadult and adult white sharks (Carcharodon carcharias)

Satellite linked radio transmitting (SLRT) tags provide long-term, high accuracy, near real-time tracking data for marine wildlife. Adult white sharks (Carcharodon carcharias Linnaeus, 1758) in the northeastern Pacific at both Guadalupe Island, Mexico and Southeast Farallon Island, USA were tagged with SLRT oval and inline finmout tags. These tags provided up to 7.4 yrs of tracking data. A previous study showed structural dorsal fin damage for SLRT tagged juvenile and subadult white sharks off South Africa. Sharks tagged in the northeastern Pacific were resighted between 1 and 11 yrs post tagging and included 10 adults and 2 subadults. Sharks that were resighted did not exhibit significant fin deformation, although in one case the oval finmount tag did cause bending of the dorsal fin due to tag shape, weight, and placement of the tag on the dorsal fin. Four inline tags came off after deployments of at least 2.2 to 3.7 yrs (based on date of last message received), and two of these caused a tear to the trailing edge of the dorsal fin upon release. Overall, SLRT tags provided long-term tracking data and there was no apparent impact on the behavior or migration cycles of the sharks. Serious dorsal fin deformation seems to occur in the case of juvenile and subadult white sharks where the fin is rapidly growing and thus for tracking juvenile white sharks, alternate methods should be considered.

Overhauling Ocean Spatial Planning to Improve Marine Megafauna Conservation

Tracking data have led to evidence-based conservation of marine megafauna, but a disconnect remains between the many 1000s of individual animals that have been tracked and the use of these data in conservation and management actions. Furthermore, the focus of most conservation efforts is within Exclusive Economic Zones despite the ability of these species to move 1000s of kilometers across multiple national jurisdictions. To assist the goal of the United Nations General Assembly’s recent effort to negotiate a global treaty to conserve biodiversity on the high seas, we propose the development of a new frontier in dynamic marine spatial management. We argue that a global approach combining tracked movements of marine megafauna and human activities at-sea, and using existing and emerging technologies (e.g., through new tracking devices and big data approaches) can be applied to deliver near real-time diagnostics on existing risks and threats to mitigate global risks for marine megafauna. With technology developments over the next decade expected to catalyze the potential to survey marine animals and human activities in ever more detail and at global scales, the development of dynamic predictive tools based on near real-time tracking and environmental data will become crucial to address increasing risks. Such global tools for dynamic spatial and temporal management will, however, require extensive synoptic data updates and will be dependent on a shift to a culture of data sharing and open access. We propose a global mechanism to store and make such data available in near real-time, enabling a holistic view of space use by marine megafauna and humans that would significantly accelerate efforts to mitigate impacts and improve conservation and management of marine megafauna.

Closed Loop Control of an MR-Conditional Robot with Wireless Tracking Coil Feedback.

This paper presents a hardware and software system to implement the task space control of an MR-conditional robot by integrating inductively coupled wireless coil based tracking feedback into the control loop. The main motivation of this work is to increase the accuracy performance and address the system uncertainties in the practical scenarios. We present the MR-conditional robot hardware design, wireless tracking method, and custom-designed communication software for real-time tracking data transfer. Based on these working principles, we fabricate the robot platform and evaluate the complete system with respect to various performance indices, i.e. data communication speed, targeting accuracy, tracking coil resolution, image quality, temperature variation, and task space control accuracy for static and dynamic targeting inside MRI scanner. The in-scanner targeting results show that the MR-conditional robot with wireless tracking coil feedback achieves the targeting error of 0.17 ± 0.08mm, while the error calculated from the joint space optical encoder feedback is 0.68 ± 0.19mm.

High-accuracy multi-camera reconstruction enhanced by adaptive point cloud correction algorithm

Multi-camera schemes can effectively increase the perception range of vision systems compared to single-camera schemes and are common in many optical applications. Unavoidable errors emerge in the global multi-camera calibration process, however, such as manufacturing error of the optical devices and computational error from marker detection algorithms, which drive down the accuracy of the camera system correlation. This paper discusses the causes of global calibration errors in detail. A four-camera vision system was built to obtain the visual information of targets including static objects and a dynamic concrete-filled steel tubular (CFST) specimen. Local calibration and global calibration were applied successively to realize multi-camera correlation, followed by filtering and stitching operations to acquire filtered global point clouds. A point cloud correction algorithm is designed accordingly to optimize the stitched point cloud structures and further improve the accuracy of the reconstructed surfaces. Based on the density features of the targets themselves (rather than standard calibration markers), the proposed point cloud correction algorithm is effective for various targets and adaptive under dynamic conditions. The point clouds and corresponding reconstructed models are shown to be more accurate after the proposed enhancement process. The point cloud correction algorithm also has strong adaptability to different static targets with complex surfaces and performs well under uncertain geometric changes and vibration. The results presented here provide both theoretical and practical support for advancements in multi-vision applications such as optical measurement, real-time target tracking, quality monitoring, and surface data acquisition.

The Clinical and Dosimetric Impact of Real-Time Target Tracking in Pancreatic SBRT

Motion often hinders the safe delivery of ablative doses of radiation in the treatment of pancreatic tumors. Real-time tumor-tracking methods are an emerging technique to increase the accuracy of delivery. In this study, we report on a large, retrospective cohort of pancreatic patients treated with real-time, fiducial-based, kV-image guidance of stereotactic body radiation therapy (SBRT). The purpose of our study was to determine the impact of real-time tracking on treatment accuracy, tumor dose, and clinical workflow. Real-time tracking data from 68 patients treated with pancreatic SBRT were analyzed. The kV images orthogonal to the treatment beam were acquired in real time during treatment to visualize the location of implanted fiducial markers. Positional corrections were made if the fiducial markers were observed >3mm from the expected reference position. We recorded the frequency and nature of treatment interventions resulting from real-time tracking and derived a neural network-based dosimetric model to calculate the impact of these in-treatment interventions on target dose. Treatment pauses that required patient realignment because of real-time tumor tracking occurred during 32% of all fractions. The median magnitude of realignment shifts was 5.2mm (range, 2.1-18.9mm). Forty-five percent of shifts resulted in dosimetric differences to the tumor; of these, the median point dose difference was 23%±22% of prescription dose (maximum, 94%). The number of pauses per fraction was significantly higher in patients treated with respiratory gating (vs abdominal compression) and in patients with greater treatment time. Fiducial-based, real-time target tracking is clinically feasible for pancreatic SBRT treatment. Our data indicate that real-time tumor tracking leads to patient realignment in 32% of cases and results in significant benefits to target coverage. The increased accuracy of real-time target tracking may potentially enable safe dose escalation in pancreatic SBRT.