Real-time Tracking Technology Research Articles

Fisherman Border Crossing Alert System using IoT

The Fisher Man Border Crossing Alert System is a innovative solution designed to enhance the safety and security of fishermen operating near maritime borders. The system integrates real-time tracking technology with border surveillance data to provide timely alerts to fishermen when they approach or cross maritime borders. Fishermen are forced to accidently cross borders where they run the risk of being murdered or captured. It is difficulty in identifying the marine borders between countries. The system is intended to prevent such accidents and to warn fisherman about border areas in advance. Maximum risks occur for fishermen in situations where they travel on a boat for fishing. In some situations, they should not move after some point and they should not enter into other countries area. It can be extensively used by people in the Sea border to find the path to reach the destination. The notification will be sent to the border security forces which act as the server to all other devices that are operated by people in ships. The fishermen crosses the sub border then the warning signal is given to both the countries and alarm is indicated to fisher men

FINCHILD: The Missing Child Finder Application

"FINCHILD" is an innovative and user-friendly mobile application designed to address the critical issue of missing children by leveraging real-time tracking technology. The application aims to empower parents, guardians, and law enforcement agencies with an effective tool to locate and recover missing children swiftly and efficiently. In a world where child safety is paramount, FINCHILD fills a significant gap by harnessing the power of real-time location tracking, geofencing, and community engagement. The application provides a comprehensive platform that integrates the latest advancements in mobile technology and data analytics to ensure a rapid and coordinated response in the event a child goes missing. The FINCHILD application is a cutting-edge real-time solution designed to address the critical issue of missing children. Leveraging advanced technologies, including GPS tracking, facial recognition, and real-time data analytics, FINCHILD aims to significantly reduce the response time and enhance the efficiency of locating missing children. Key Words: GPS Tracking, Facial Recognition, Real-Time Alerts, Community Engagement.

Resilient Chain: AI-Enhanced Supply Chain Security and Efficiency Integration

In most recent time, the global landscape of supply chain management has experienced unprecedented challenges during the COVID-19 pandemic, which has significantly impacted the routine and smooth operations of different firms in the United States. This paper explains about the importance of artificial intelligence (AI) and machine learning (ML) in the mitigation of these disruptions and possible ways of improving supply chain security and its efficiency. This research adopted a questionnaire survey involving 281 managers, with the aim to comprehensively examine the current state of AI integration across the U.S. supply chain sector, with focus on some key components like real-time tracking, cost optimization, and risk management. A mixed method approach was adopted for this research, utilizing both inferential and descriptive analyses to unravel insights and trends into the role of AI in enhancing supply chain security. The results indicate that integrating AI, most especially through cost optimization, real-time tracking, and risk management components, emerges as a significant determinant of supply chain security in the United States. Real-time tracking technologies are identified as crucial for monitoring shipments and assets, enabling quick responses to security incidents, and ensuring end-to-end visibility throughout the supply chain. Despite the potential benefits, the study highlights challenges that hinder the widespread integration of AI technologies in the U.S. supply chain. The high cost of AI adoption and the limited availability of skilled personnel are major obstacles. To address these challenges, the paper proposes practical recommendations. Firstly, real-time tracking technologies are recommended to monitor shipments and assets, facilitating rapid responses to security incidents, and ensuring visibility across the entire supply chain. Furthermore, the paper suggests optimizing costs by investing in cost-effective security solutions. This includes leveraging AI for automated monitoring systems and adopting secure packaging measures. These strategies aim to minimize vulnerabilities without compromising security standards, offering a balanced approach to enhancing supply chain security while mitigating the financial implications associated with AI adoption.

FINCHILD: Real Time Missing Child Finder Application

Abstract: "FINCHILD" is an innovative and user-friendly mobile application designed to address the critical issue of missing children by leveraging real-time tracking technology. The application aims to empower parents, guardians, and law enforcement agencies with an effective tool to locate and recover missing children swiftly and efficiently. In a world where child safety is paramount, FINCHILD fills a significant gap by harnessing the power of real-time location tracking, geofencing, and community engagement. The application provides a comprehensive platform that integrates the latest advancements in mobile technology and data analytics to ensure a rapid and coordinated response in the event a child goes missing. The FINCHILD application is a cutting-edge real-time solution designed to address the critical issue of missing children. Leveraging advanced technologies, including GPS tracking, facial recognition, and realtime data analytics, FINCHILD aims to significantly reduce the response time and enhance the efficiency of locating missing children.

Unmanned aerial vehicle reconnaissance image recognition based on convolutional neural network

The important strategic position of military UAVs and the wide application of civil UAVs in many fields, they all mark the arrival of the era of unmanned aerial vehicles. At present, in the field of image research, recognition and real-time tracking of specific objects in images has been a technology that many scholars continue to study in depth and need to be further tackled. Image recognition and real-time tracking technology has been widely used in UAV aerial photography. Through the analysis of convolution neural network algorithm and the comparison of image recognition technology, the convolution neural network algorithm is improved to improve the image recognition effect. In this paper, a target detection technique based on improved Faster R-CNN is proposed. The algorithm model is implemented and the classification accuracy is improved through Faster R-CNN network optimization. Aiming at the problem of small target error detection and scale difference in aerial data sets, this paper designs the network structure of RPN and the optimization scheme of related algorithms. The structure of Faster R-CNN is adjusted by improving the embedding of CNN and OHEM algorithm, the accuracy of small target and multitarget detection is improved as a whole. The experimental results show that: compared with LENET-5, the recognition accuracy of the proposed algorithm is significantly improved. And with the increase of the number of samples, the accuracy of this algorithm is 98.9%.

Ordering Policy of Two-Stage Newsvendor Model for Fresh Retailer under RFID Investment

Fresh products have a strong dependence on time and a large loss rate in the circulation process. Applying RFID technology to the supply chain of fresh products, through the real-time tracking technology, can not only reduce the products’ time dependence but also realize the second order within the whole sales period. This paper takes a two-echelon fresh supply chain of a single fresh retailer as the research object, constructs a two-stage Newsvendor model with or without RFID technology, compares the difference in profits, and provides decision-making reference for fresh retailers whether to invest in RFID or not.

An integrated augmented reality surgical navigation platform using multi-modality imaging for guidance.

An integrated augmented reality (AR) surgical navigation system that potentially improves intra-operative visualization of concealed anatomical structures. Integration of real-time tracking technology with a laser pico-projector allows the surgical surface to be augmented by projecting virtual images of lesions and critical structures created by multimodality imaging. We aim to quantitatively and qualitatively evaluate the performance of a prototype interactive AR surgical navigation system through a series of pre-clinical studies. Four pre-clinical animal studies using xenograft mouse models were conducted to investigate system performance. A combination of CT, PET, SPECT, and MRI images were used to augment the mouse body during image-guided procedures to assess feasibility. A phantom with machined features was employed to quantitatively estimate the system accuracy. All the image-guided procedures were successfully performed. The tracked pico-projector correctly and reliably depicted virtual images on the animal body, highlighting the location of tumour and anatomical structures. The phantom study demonstrates the system was accurate to 0.55 ± 0.33mm. This paper presents a prototype real-time tracking AR surgical navigation system that improves visualization of underlying critical structures by overlaying virtual images onto the surgical site. This proof-of-concept pre-clinical study demonstrated both the clinical applicability and high precision of the system which was noted to be accurate to <1mm.

Real-time resource tracking for analyzing value-adding time in construction

Abstract Improving the effectiveness of production control has attracted the interest of researchers and lean construction practitioners over recent years, through techniques such as Last Planner System (LPS) and Location-based Management System (LBMS). However, in these techniques, data collection and analysis still remain manual. Remotely locating workers on site has been suggested as a potential technology to collect crucial data required for production control. The purpose of this study is to test the applicability of a real-time tracking system for collecting data for production control in different types of construction projects. We applied Bluetooth Low Energy (BLE) technology in real-time tracking of workers in three case projects, including residential, office building, and plumbing renovation. We compared various tracking device placement strategies and analyzed the share of uninterrupted presence of workers in work locations based on the collected data. The findings show that both location-based and time-based information of workers can be obtained in real time from the proposed system, but issues of accuracy and coverage need to be considered when defining the data collection plan for each project. Accuracy and coverage issues can be resolved to a significant degree by applying heuristics in data analysis rather than investing in a more sophisticated tracking technology. The conclusion is that real-time tracking technologies are ready for implementation when certain heuristics and guidelines for installation are followed. It is possible to calculate a real-time presence index on a construction site. These data could be used to evaluate the impact of construction management interventions on waste on-site.

All-optical imaging and tracking technology for rectilinear motion targets through scattering media

Light scattering is a main factor that restricts optical transmission and deteriorates optical imaging performance. All-optical imaging for moving targets through complex scattering media is one of the most challenging techniques. In this paper, a method for real-time tracking of moving targets through scattering medium is presented by utilizing optical memory-effect and autocorrelation of speckle difference. In the experiment on imaging through a scattering medium, an object is hidden at a distance u behind a highly scattering medium. The object is illuminated by a spatially incoherent pseudothermal light source. The light is diffused through the scattering medium. Camera placed at a distance u0 on the other side of the medium records the pattern of the scattered light. According to the theory of optical memory-effect, the process of scattering imaging is a convolution process of point spread function (PSF) and object. In the procedure of object moving, the scattered signals from two frames are captured. The background noise could be removed by subtracting the two captured image. Then, the autocorrelation operation calculates the speckle difference, and hidden targets can be effectively reconstructed with the phase retrieval algorithm. The experiment demonstrates the imaging of targets with different speeds. The results have shown that the faster the speed, the worse the imaging quality is. High-speed moving objects can be imaged by using a high frame rate camera to reduce the exposure time or by disambiguating the speckle pattern. In subsequent experiments, the distance of the target movement is calculated with the magnification of the system. The collected two frames of speckle must be within the same memory effect angle. Only in this way can the calculation accuracy of the motion distance be guaranteed. With the moving of the target, the cross-correlation information of the target appears at different positions of the speckle difference autocorrelation map. Finally, according to the cross-correlation of the target at different locations, the real-time tracking of the moving target can be realized. Due to the Gaussian distribution of the laser beam, the cross-correlation intensity of the speckle difference autocorrelation map decreases with the object moving further. Therefore the target moving range is limited by the laser beam diameter, intensity distribution and camera field angle. It is verified experimentally that the imaging and tracking of moving targets which are hidden behind the ground glass can be achieved successfully by using this method. This kind of imaging and real-time tracking technology for targets moving through the scattering medium has important potential applications in biomedicine and other fields.

Risk-based look-ahead workspace generation for earthwork equipment using near real-time simulation

The construction industry accounted for more than 17% of fatal work injuries, i.e., 806 counts of death, in the U.S. in 2012. Approximately 75% of struck-by fatalities in the construction industry are reported to have been caused by heavy equipment. Researchers have addressed the need for the enhanced safety of earthwork equipment in two different streams, namely using advanced planning methods to avoid overlaps between the workspaces of different activities of equipment or using real-time tracking technologies to avoid the collision between equipment in the immediate future. However, none of these solutions enables the equipment to reliably predict the operation of other pieces of equipment for a long-enough time window to find a collision-free path using path re-planning. Accordingly, the present paper proposes a novel method to generate risk maps based on the integration of the pose and state data of the equipment with near-real-time simulation and considering the proximity-based and visibility-based risks. These risk maps are used to define dynamic workspaces that can in turn be used to perform path re-planning in a timely manner. The proposed method is implemented and tested in a case study. In light of the results of the case study, it is found that the proposed method is providing a reliable basis for the safety analysis of earthwork sites by generating workspaces with different levels of risk that can be used to provide timely alerts to different equipment and crews.

A labor consumption measurement system based on real-time tracking technology for dam construction site

Abstract The aim of the study presented in this paper is the development of a labor consumption measurement system based on real-time tracking technology for use on a dam construction site. Such technology includes Global Positioning System (GPS), and Geographic Information System (GIS). The system is three-layered and aims to solve several labor computational and usability challenges. The software for processing the collected data, presenting real-time site state visualization, and the accurate analysis of on-site labor consumption is run by smart phones with GPS devices, on-site private wireless base stations, and servers. The benefits of this quantitative labor consumption measurement approach for hydropower projects include the provision, for each dam monolith, of precise information regarding both the number and category of laborers together with their respective working hours. Such knowledge provides adequate quality management information for the owner and the supervisor and importantly aids payment negotiations with contractors. The proposed system was firstly applied to the world's third largest hydropower project. On-site tests successfully demonstrated the feasibility and effectiveness of the whole system. The results achieved show that the system is able to log entire on-site trajectories of laborers, and calculate the accurate labor consumption of each dam monolith.

Validating Bluetooth logging as metric for shopper behaviour studies

The ability to track shoppers as they move through retail environments using signals emitted by their communication devices kindles the interest of practitioners and researchers. This data collection method is cheap and has the ability to supply big data for shopper insights. However, this non-probabilistic sampling method can possibly under- or over-represent certain groups of the shopper population. This study assesses the validity of the data describing the length of shopping trips and representativeness of the sample of shoppers carrying Bluetooth-enabled devices. The authors track unique Bluetooth logs in-store and compare to simultaneously collected data from a manual, systematic sample of 324 shoppers observed and interviewed in the same supermarket. A comparison of the results obtained from the two samples (auto-logging and manual systematic) drawn from the same population indicates automated Bluetooth tracking produces very similar (r=.92, p<.001) trip lengths to that observed manually. Basket size, spend and occupation of Bluetooth trackable shoppers are similar to those with no Bluetooth-enabled devices. These findings present compelling evidence that the Bluetooth auto-logging method holds great potential for retail practice and research. An expected under-representation of the oldest demographic (66 y.o. and over) in the Bluetooth discoverable sample calls for complementary methods of data collection to minimise representation bias in real-time tracking technologies for shopper research. The benefits of using auto-logging data describing shopping trip length for retail practitioners and researchers are discussed.

A Supervisor Management and Evaluation System Based on Real-Time Location System

Effective management and evaluation of on-site supervision staffs in large hydropower project is a key method to strengthen management, improve efficiency, and ensure the progress and quality of projects. A new method based on smart phones and real-time tracking technology was developed to manage and evaluate on-site supervision staffs. The location information of supervisors at the construction site is collected and uploaded to the server by smart phones containing a GPS data uploading application. The server stores and processes the data, and displays the location and the track of staffs on the web page to achieve real-time monitoring. The collected GPS data is deeply analyzed to identify the specific work context of supervisors and to build 3 indicators: Field Work Time, Effective Work Time and Effective Work Scope which are effective indicators to measure the workload. The feasibility of the method was verified by simulation experiments. Experimental results show that the proposed method can determine the real-time position of supervisors accurately, and identify their work contexts effectively. Extracted indicators meet the realities of situation. The method possesses abroad potential in large hydropower construction management.

Kinematics Model and Simulation of Precise Wheat-Sowing Robot

The wheat precise seeding technology is an effective way to increase the production of wheat. Walking precision of the agricultural machinery combined with precise seeders has a directly effect on the accuracy of sowing. The real-time tracking technology has become the main problem in agricultural fields. In this paper, the kinematics model of a mobile robot was established and MATLAB was used to make simulation analysis of Path tracking. The results meet the requirements of the robot path tracking and provide technical support for precision seeding.

Visualization and Real-time Tracking Technologies of the Probe Used in Surgical Navigation Based on Electromagnetic Positioning

The visualization and real-time tracking technologies of the probe in surgical navigation system are studied.The electromagnetic positioning method is introduced,and the probe with data acquisition function is designed based on electromagnetic positioning.Firstly,the probe model is constructed by means of three-dimensional solid modeling technology, and the transformation from the solid geometry model to the three-dimensional surface models is completed.Secondly,the probe tip is registered using the pivot calibration method and the registration accuracy is also tested.Then,the registration between the CT model and the patients site is realized intraoperatively by means of iterative closest point(ICP) algorithm, and simulation analysis and accuracy verification are carried out.Finally,according to the preoperatively registered position and orientation,the spatial location of the probe is tracked in real-time and accurately,and is displayed in the system.The results show that the data acquisition function and registration accuracy of the probe,as well as the effect of registration algorithms can meet the needs for surgical navigation.

Quantifying Respiratory-induced Prostate Motion using Continuous Real-time Tracking Technology

Prostate positional variability can alter the effectiveness of radiation therapy when precise target location is unknown. Traditionally, PTV margins are designed to compensate for inter-fraction prostate setup variability. PTV margins may be reduced when using daily image-guidance. More recently, the dosimetric relevance of intra-fraction prostate motion has been recognized, and may be compensated for by continuous real-time adaptive radiation therapy afforded by the Calypso® 4D Localization System. As of today, sparse data is available regarding the magnitude and clinical relevance of highfrequency respiratory-induced prostate motion. The specific aim of this analysis was to quantify respiratory-induced prostate motion using electromagnetic continuous real-time tracking technology.

Speed and amplitude of lung tumor motion precisely detected in four-dimensional setup and in real-time tumor-tracking radiotherapy

To reduce the uncertainty of registration for lung tumors, we have developed a four-dimensional (4D) setup system using a real-time tumor-tracking radiotherapy system. During treatment planning and daily setup in the treatment room, the trajectory of the internal fiducial marker was recorded for 1 to 2 min at the rate of 30 times per second by the real-time tumor-tracking radiotherapy system. To maximize gating efficiency, the patient's position on the treatment couch was adjusted using the 4D setup system with fine on-line remote control of the treatment couch. The trajectory of the marker detected in the 4D setup system was well visualized and used for daily setup. Various degrees of interfractional and intrafractional changes in the absolute amplitude and speed of the internal marker were detected. Readjustments were necessary during each treatment session, prompted by baseline shifting of the tumor position. The 4D setup system was shown to be useful for reducing the uncertainty of tumor motion and for increasing the efficiency of gated irradiation. Considering the interfractional and intrafractional changes in speed and amplitude detected in this study, intercepting radiotherapy is the safe and cost-effective method for 4D radiotherapy using real-time tracking technology.