Advances In Tracking Technology Research Articles

Woodlog Inventory Optimization using Object Detection and Object Tracking

In the timber industry, keeping track of wood stacks is crucial to avoid stockpiles that are too large or too small ensuring efficient operations. Traditional methods are often time-consuming and inaccurate, leading to inefficiencies. This research proposes a novel solution for timber yard inventory management using cutting-edge technology.The approach utilizes YOLOv8, a powerful object detection algorithm, to identify wood logs in live video feeds. DeepSORT, a tracking algorithm, then follows these identified logs over time. This automation eliminates the need for manual tracking, minimizes errors, and enforces the "First-In-First-Out" (FIFO) principle for efficient inventory use.The study also compares DeepSORT to other tracking algorithms like OC-SORT and ByteTrack to identify the most effective option for this specific application. The results demonstrate that the proposed method significantly improves detection accuracy and reliability, leading to better inventory management.In essence, this research highlights how integrating advanced detection and tracking technologies can revolutionize timber yard operations. By automating processes and ensuring accurate inventory control, these technologies can significantly reduce costs and boost overall efficiency in the timber sector.

The Role of Urban Disaster Risk Management in Major Catastrophic Events: A Case Study of Resilience in Chinese Cities During the COVID-19 Pandemic

The emergence of infectious diseases has historically influenced urban development, necessitating the evolution of urban planning toward greater disaster resilience. The COVID-19 pandemic, in particular, has revealed weaknesses in modern urban planning and governance, emphasizing the need for enhanced urban resilience and disaster risk management. For China, as urban populations continue to grow, urban resilience and disaster risk management have become focal points for urban planners and policymakers, ensuring that cities can rapidly adapt and effectively respond to various challenges. This study summarizes a series of emergency measures adopted by the Chinese government during the COVID-19 pandemic and analyzes their effectiveness. China's response, characterized by early intervention, social distancing, extensive testing, and advanced tracking technologies, effectively curtailed the virus's spread, especially in Hubei province and its capital, Wuhan. Despite these successes, the paper identifies areas where China's urban resilience could be improved, including coordination of emergency plans, information dissemination, and social cohesion, among other aspects, to better confront future challenges.

Energy Production Optimization by Positioning of Solar Panels and Surveillance System with Cleaning of Panels

The pursuit of efficient and sustainable energy generation has led to the widespread adoption of solar panels. However, the optimal performance of these panels can be hindered by factors such as dirt accumulation, suboptimal orientation, and security concerns. To address these challenges, we propose an integrated Solar Panel Tracking, Cleaning, and Surveillance System (SPTCSS). Our system employs advanced tracking technology to optimize solar panel orientation, ensuring maximum exposure to sunlight throughout the day. Additionally, it incorporates automated cleaning mechanisms, utilizing water and brushes to remove dust, debris, and other contaminants, thereby maintaining peak efficiency. Furthermore, the surveillance aspect of the system provides real-time monitoring and security features, safeguarding against theft, vandalism, and unauthorized access. Through a network of sensors and cameras, any anomalies or suspicious activities can be promptly detected and addressed. By integrating tracking, cleaning, and surveillance functionalities into a single system, our solution offers a comprehensive approach to enhancing the performance, longevity, and security of solar panel installations. This not only maximizes energy generation but also minimizes maintenance requirements and mitigates risks, ultimately contributing to a more sustainable and reliable renewable energy infrastructure

Research on Evaluation and Optimization Algorithm of Athletes' Sports Skills Based on Trajectory Analysis and Machine Learning

Evaluating athletes' sports skills is significant for optimizing their training strategies and improving competitive outcomes. Although various studies are done to assess athletes' skills, they face challenges because of their limitations in capturing the complex, intricate patterns in athletes' movements. Hence, we proposed an innovative approach utilizing trajectory analysis and machine learning algorithms to evaluate and optimize athletes' sports skills. Initially, the trajectory data is collected using advanced motion tracking technology during either training or competitive sessions of the athletes. The collected data was pre-processed, and then feature extraction was performed to extract the most important and relevant features within the data. Further, the Gradient Boosting Decision Tree (GBDT) was trained using the extracted features to predict the athletes' performances. The GBDT is a powerful machine learning algorithm that can handle complex, non-linear interconnections among variables, enabling it to accurately predict the athletes' performances. Finally, we applied the Whale Optimization Algorithm (WOA) to refine the training process of the GBDT, enabling precise training and accurate predictions. The proposed methodology was implemented in the MATLAB software, and it is validated using the real-world athlete data collected during training sessions. The experimental results are validated in terms of parameters such as accuracy, precision, recall, and f-measure. Furthermore, we made a comparative study with the existing methods to validate the effectiveness and robustness of the proposed technique.

Comparative Analysis Of A Multi-Layered Weapon System For City Air Defense In The Modern Warfare

In the era of modern warfare, urban defense is a very important aspect to maintain the security and stability of a country. Because modern war is a non-military war in which developed countries and foreign countries try to destroy a country through ideological, political, social, cultural and security defense. To protect the territory with effective air defense, it takes a strong and sophisticated defense resources with a reliable range of surveillance and agility to destroy any effort that threatens the security and sovereignty of the country. To achieve the objective of building a more efficient air defense system and functioning alongside other air defense platforms, new ideas and thinking are needed for program planning and the requirements of medium-range missile systems when building an air defense system. The research method used in this research is descriptive qualitative through a literature study. In the literature review, it is necessary to conduct a thorough search to ensure that the literature sources used are truly relevant to the research topic and a comparative analysis approach is used. In the realm of analyzing layered weapon systems, such as Hisar O, Hisar A, Korkut Gun System, Iron Dome, and NASAMS, it becomes imperative to delve into the comparative analysis and interpret the implications of their similarities and differences. Hisar O, a sophisticated air defense system, showcases advanced capabilities designed to counter aerial threats. Its cutting-edge technology and robust infrastructure provide a formidable defense mechanism. On the other hand, Hisar A, another component of the layered defense, excels in short-range air defense, ensuring effective protection against low-altitude aerial targets. Korkut Gun System, presents a unique blend of artillery and air defense capabilities. Its adaptable nature allows it to provide ground forces with enhanced protection against a wide range of threats. Iron Dome system has gained international recognition for its exceptional performance in countering short-range rocket threats. This innovative system incorporates advanced tracking and interception technologies, enabling it to neutralize incoming projectiles with a high success rate. NASAMS (Nationals Advanced Surface-to-Air Missile System) stands out as a versatile air defense solution. Its state-of-the-art radar and missile technologies ensure reliable protection against a variety of airborne threats, including aircraft, helicopters, and unmanned aerial vehicles (UAVs). Now, let's delve into the implications of these comparative analyses for Indonesia. By understanding the strengths and weaknesses of each system, Indonesian defense strategists can make informed decisions regarding their defense capabilities. This analysis assists in identifying potential gaps in the country's air defense network and formulating strategies to address them effectively. In conclusion, through a comparative analysis of layered weapon systems such as Hisar O, Hisar A, Korkut Gun System, Iron Dome, and NASAMS, we gain valuable insights into their capabilities and implications. evaluating differences and similarities, can help Indonesian defense planners make informed decisions to strengthen city air defense systems in the modern warfare.

The causes and implications of sex role diversity in shorebird breeding systems

Males and females often exhibit different behaviours during mate acquisition, pair‐bonding and parenting, and a convenient label to characterize these behaviours is sex role. The diverse roles that male and female shorebirds (plovers, sandpipers and allies) exhibit in mating and parenting have played a key role in advancing mainstream theories in avian ecology and behavioural biology including sexual selection, sexual conflict and parental cooperation. Recent advances in shorebird research have also highlighted the significance of the social environment in driving sex role behaviours by linking the adult sex ratio with breeding behaviour and population demography. Here we review the key advances in sex role research using shorebirds as an ecological model system. We identify knowledge gaps and argue that shorebirds have untapped potential to accelerate diverse research fields including evolutionary genomics, movement ecology, social networks and environmental changes. Future studies of sex roles will benefit from individual‐based monitoring using advanced tracking technologies, and from multi‐team collaborations that are facilitated by standardized data collection methodologies across different species in the field. These advances will not only contribute to our understanding of reproductive strategies, but they will also have knock‐on effects on predicting population resilience to environmental changes and on prioritizing species for conservation.

Using high-resolution GPS data to create a tourism Intensity-Density Index

Technological developments over the last two decades have allowed researchers to employ advanced tracking technologies to collect high-resolution spatial and temporal data. Despite the extensive use of these technologies in tourism research, they have not yet been applied to the existing indicators of tourism demand. The current paper aims to fill this lacuna, proposing the use of tracking technologies to measure tourist activity in destinations and, in particular, extreme conditions such as tourist saturation and overtourism. It introduces a new index for tourism demand, the Intensity-Density Index (IDI), based on high-resolution data in time and space. After presenting an overview of the common indicators for measuring tourism demand, the most common indicators, the Tourism Intensity Rate (TIR) and the Tourism Density Rate (TDR), are calculated twice, using traditional methods and advanced tracking technologies. The second calculation is based on a unique survey conducted in Israel between 2015 and 2017, which included some 3,000 tourists whose activity in the destination was documented entirely on a national level and at high resolution. Finally, the methodology for calculating high-resolution (HR) indicators using GPS data is presented, resulting in the IDI. Advanced tracking technologies’ use in calculating the IDI not only helps present tourism activity more accurately in terms of time and space but can also be applied in tourism management to serve as a tool for effective planning.

Soldier Tracking and Health Monitoring System

The Soldier Tracking and Health Monitoring System is a comprehensive solution designed to enhance the safety, efficiency, and well-being of soldiers in military operations. This system combines advanced tracking technologies with health monitoring capabilities to provide real-time situational awareness and vital sign monitoring for individual soldiers. Overall, this system provides a comprehensive solution for tracking soldiers' locations and monitoring their health in real-time. By combining advanced tracking technologies with health monitoring capabilities, it aims to enhance the effectiveness and safety of military operations while ensuring the well-being of individual soldiers.

Wide-area vehicle trajectory data based on advanced tracking and trajectory splicing technologies: Potentials in transportation research

Trajectory data of road users play a crucial role in transportation engineering and traffic safety research. Previous vehicle trajectory data, including naturalistic driving data, trajectory data captured by drones and traffic cameras, have greatly promoted the research of traffic safety, traffic simulation, and other transportation engineering fields. However, existing technologies in collecting trajectory data are limited their detection range. With the development of the sensing and tracking technologies, it is possible to track the trajectory information of road users at the wide-area level, i.e., the real-time trajectory data of all road users on the entire road. Recently, we published our data sharing platform, Tongji Road Trajectory Sharing (TJRD TS, available online at https://tjrdts.com) Platform, providing our open wide-area vehicle trajectory data for researchers, academics, and road traffic professionals. Advanced vehicle tracking and trajectory splicing technologies, such as millimeter wave radar and edge computing technology, were employed to obtain such wide-area vehicle trajectory data. In this short communication article, we brainstorm ideas of using wide-area vehicle trajectory data in traffic safety research, traffic efficiency research, and connected and autonomous vehicle (CAV) application. We hope this short communication and our published data sharing platform can serve as the steppingstone for those who are interested in road transportation engineering and road safety research using such wide-area vehicle trajectory data.

Tracking and Monitoring Technologies to Support Airport Construction Safety

This paper discusses how advanced tracking and monitoring technologies can be used to increase safety for construction activities at airports. Airport construction is a significant infrastructure sector and in 2020 the Airport Improvement Program funded $300 million for airport projects in the United States. This includes funding for pavement reconstruction, airfield upgrades to meet current standards (e.g., wider runways), the construction of new terminal facilities, and additional capacity (e.g., new runways). The airfield environment presents special hazards for constructors, including proximity to active aircraft operations, and the requirement to comply with many additional rules such as those required by Federal Aviation Administration (FAA) and the Transportation Security Agency (TSA); many of these rules are required to ensure safety and security. Airport construction activities require close oversight, additional inspections by airport operations personnel, and stringent rules regarding access and operation in different areas of the airfield. Access and operating requirements affect both construction workers and construction equipment, and there are often different rules for different areas at the airport. One of the most restricted areas on an airport is the runway. Access to the runway and the safety area around a runway requires explicit permission from Air Traffic Control (ATC). If a vehicle or pedestrian (or aircraft) crosses the boundary without permission, it is considered a runway incursion. A runway incursion could cause a major incident at the airport and could result in injuries and fatalities. Runway incursion events are recorded by the FAA and represent a serious safety violation for the airport. Runway incursions and the technology to prevent incursions are discussed as an example that illustrates the need for and benefits of accurate monitoring of construction equipment and personnel. Technologies that may be used to enhance tracking and support situational awareness are present to illustrate the possible ways that enhanced monitoring can be used at an airport. Solutions may include the use of advanced technologies such as real-time vehicle location sensors, which may be combined with robust electronic maps to enhance safety for construction equipment and personnel location in the airfield environment. A discussion of opportunities and challenges of these systems is detailed.

Cookies ‘n’ Consent: An empirical study on the factors influencing of website users’ attitude towards cookie consent in the EU.

Since GDPR came into enforcement in 2018, various firms have been found violating or circumventing the ePrivacy Directive known as the Cookie Law which lays out the cookie consent guidelines for websites. To improve the GDPR compliance rate, several conversations are going on between EU commission, Data protection agencies, business & websites owners and ad vendors regarding their cookie policy, obtaining user consent for data collection and its usage. One of the key stakeholders who are the website users, whose privacy is in question seems to be left out from the discussions. The study aimed to understand user perception towards website cookie banners, which are mandatory under GDPR, and the influence of factors like awareness of cookies, user experience, consent banner design, privacy risk, brand trust on user’s willingness for accepting all cookies, to develop recommendations to improve customer’s motivations to give consent. Using a quantitative approach, the primary data was collected from 132 internet users residing in the EU region through an online survey questionnaire shared in social media networks. The results showed that the (i) majority of respondents had more than moderate level of awareness about cookies (ii) they are more likely to accept cookies for quick access or task completion, (iii) acceptance of cookies was varied across different categories of online activity and (iv) given a choice they are more likely to opt-out of 3rd party cookies which are widely used for targeted advertising. Since 3rd party cookies will be phased out in the near future and are likely to be replaced with more advanced customer tracking technologies which are harder to opt-out of, this study proposes a framework for Consent for Advertising Directive (CAD) to go beyond the existing Cookie Law, which will improve user data protection regardless of the tracking technology used, and help brands to improve transparency about their data collection and avoid GDPR violations.

Raptor research during the COVID-19 pandemic provides invaluable opportunities for conservation biology

Research is underway to examine how a wide range of animal species have responded to reduced levels of human activity during the COVID-19 pandemic. In this perspective article, we argue that raptors (i.e., the orders Accipitriformes, Cariamiformes, Cathartiformes, Falconiformes, and Strigiformes) are particularly well-suited for investigating potential ‘anthropause’ effects: they are sensitive to environmental perturbation, affected by various human activities, and include many locally and globally threatened species. Lockdowns likely alter extrinsic factors that normally limit raptor populations. These environmental changes are in turn expected to influence – mediated by behavioral and physiological responses – the intrinsic (demographic) factors that ultimately determine raptor population levels and distributions. Using this population-limitation framework, we identify a range of research opportunities and conservation challenges that have arisen during the pandemic, related to changes in human disturbance, light and noise pollution, collision risk, road-kill availability, supplementary feeding, and persecution levels. Importantly, raptors attract intense research interest, with many professional and amateur researchers running long-term monitoring programs, often incorporating community-science components, advanced tracking technology and field-methodological approaches that allow flexible timing, enabling continued data collection before, during, and after COVID-19 lockdowns. To facilitate and coordinate global collaboration, we are hereby launching the ‘Global Anthropause Raptor Research Network’ (GARRN). We invite the international raptor research community to join this inclusive and diverse group, to tackle ambitious analyses across geographic regions, ecosystems, species, and gradients of lockdown perturbation. Under the most tragic of circumstances, the COVID-19 anthropause has afforded an invaluable opportunity to significantly boost global raptor conservation.

Blockchain technology key to veracity in supply chain transaction data

Data are the foundation of the supply chain. However, the modern data stream in a supply chain is based on trust of the actors therein. Blockchain, a form of distributed ledger technology, eliminates the trust requirement of sharing supply chain data and allows each user to maintain an accurate, current copy of the ledger, without fear of data corruption or manipulation by bad actors. This paper reviews the application of blockchain to the management of transaction data in the supply chain. An overview of current blockchain technology will be discussed as well as advantages and disadvantages of the technology when applied to the supply chain. Current uses and research of the blockchain in supply chains will be discussed. There are three basic types of materials that are being explored in supply chain management using blockchain technology. The first is information-based materials and products. The most natural starting place for the blockchain is to replace the documentation and financial instruments. The second is fungible or commodity type materials. These goods are those delivered and consumed automatically, such as energy. The last are luxury, or crucial materials. These are items that are expensive or important enough that the costs of using advanced tracking technology makes economic sense.

Using geoinformatics to assess tourist dispersal at the state level

Advanced tracking technologies have facilitated the tracking of tourists' movement with high levels of spatial resolution, allowing for the exploration of factors that influence dispersal. However, the degree to which different analytical indices impact the results that they generate, remains under-researched. This study uses a high tempo-spatial resolution data set of location tracking information that was collected in the island state of Tasmania, Australia, using a mobile phone research application. It compares the results that emerge when four different analytical indicators are used to quantify tourist dispersal. The results improve understandings of the role that analytical indicators play in assessing dispersal, along with the underlying factors that influence tourists' dispersal at the state scale.

Particle size analyses of polydisperse liposome formulations with a novel multispectral advanced nanoparticle tracking technology

Liposomes are potent adjuvant constituents for licensed vaccines and vaccine candidates and carriers for drug delivery. Depending on the method of preparation, liposomes vary in size distribution, either forming uniform small size vesicles or a heterogeneous mixture of small to large vesicles. Importantly, differences in liposomal size have been demonstrated to induce differential immune responses. Determination of particle size distribution could therefore be crucial for the efficacy and stability of vaccine formulations.We compared the techniques of dynamic light scattering, laser diffraction, and conventional nanoparticle tracking analysis with a novel multispectral advanced nanoparticle tracking analysis (MANTA) for particle size determination of mono- and polydisperse liposomes. MANTA reported an average 146 nm size of monodisperse liposomes but showed a multimodal distribution of polydisperse liposomes with continuous sizes from 50 to 2000 nm. However, approximately 95% of particles were in the size range of 50–1500 nm and only few particles were identified in the 1500–2000 nm range for the investigated volume.Based on our results, we conclude that MANTA is the most suitable approach and can serve as stand-alone technique for particle size characterization of heterogeneous liposome samples in the 50–2000 nm size range.

Development of Reconfigurable Antenna for Advanced Tracking Technology

<p>This paper focuses on the design and fabrication of reconfigurable multiband antenna for RFID and GPS as an advance tracking technology for various applications that achieve a physically compact, planar profile and sufficient bandwidth. The antenna can be reconfigured as single band at 1.275 GHz for GPS applications when the switches are OFF state and dual-band frequencies at 0.915 GHz and 2.4 GHz required in RFID applications when the switches are ON state. The performance of the antenna involves changing the switches to ON or OFF mode by controlling RF switches. RF MEMs RMSW101, Single Pole Single Throw (SPST) switches have been chosen due to the satisfactory RF properties includes low insertion loss, good impedance matching and high isolation. The gain for single and dual band is greater than 2dBi. The design methodology and antenna measurement results are both presented and discussed in this letter.</p>

The Value of Pop-Up Stores in Driving Online Engagement in Platform Retailing: Evidence From a Large-Scale Field Experiment With Alibaba

We study the value of short-lived and experiential-oriented pop-up stores, a popular type of omni-channel retail strategy, on both retailers that participate in pop-up store events and retailing platforms that host these retailers. We conducted a large-scale randomized field experiment with Alibaba Group involving approximately 800,000 customers and used advanced Wi-Fi technology to track every customer’s visit to a pop-up store—a missing component from past research that commonly relies on point-of-sales data. With our field experiment and advanced tracking technology, we provide the first causal evidence that pop-up store visits substantially increase customers’ subsequent searches and purchases at participating retailers’ online stores. We also find that such effects are heterogeneous across customers: new customers showed a larger relative increase in online activities after the experiment compared to existing customers. Furthermore, from a platform perspective, we show that pop-up store visits increase customers’ searches and purchases at non-participating retailers on the same platform, which is a pleasant surprise for the platform owners. We discuss how our results can stimulate future research in omni-channel retailing and platforms, and offer implications for how to implement and optimize retail strategies surrounding pop-up stores.

A Layered Approach for More Robust Generation of Road Network Maps from Vehicle Tracking Data

Nowadays, large amounts of tracking data are generated via GPS-enabled devices and other advanced tracking technologies. These constitute a rich source for inferring the structure of transportation networks. In this work, we present a novel methodology for revealing a road network map from vehicle trajectories. Specifically, we propose an enhanced and robust map construction algorithm that is based on segmenting the original tracking data according to different types of movement and then constructing the topology of the road network hierarchically. The segmentation produces separate road network layers, which are then fused into a single network. This provides a more efficient way to addresses the challenges imposed by noisy and low sampling rate trajectories. It also allows for a mechanism to accommodate automatic map maintenance on updates. Thus, the proposed approach overcomes the limitations of existing methods and introduces a map construction algorithm that is robust against heterogeneous and sparse data and capable to incorporate changes and improvements. An experimental evaluation extensively assesses the quality of the proposed methodology by constructing large parts of the road networks of four major cities, namely Athens, Berlin, Vienna, and Chicago, using as input GPS tracking data of utility vehicles and taxi fleets. Our results show significant improvements concerning the spatial accuracy and the quality of the constructed road network over the current state of the art.

Early detection of vessel delays using combined historical and real-time information

In ocean transportation, detecting vessel delays in advance or in real time is important for fourth-party logistics (4PL) in order to fulfill the expectations of customers and to help customers reduce delay costs. However, the early detection of vessel delays faces the challenges of numerous uncertainties, including weather conditions, port congestion, booking issues, and route selection. Recently, 4PLs have adopted advanced tracking technologies such as satellite-based automatic identification systems (S-AISs) that produce a vast amount of real-time vessel tracking information, thus providing new opportunities to enhance the early detection of vessel delays. This paper proposes a data-driven method for the early detection of vessel delays: in our new framework of refined case-based reasoning (CBR), real-time S-AIS vessel tracking data are utilized in combination with historical shipping data. The proposed method also provides a process of analyzing the causes of delays by matching the tracking patterns of real-time shipments with those of historical shipping data. Real data examples from a logistics company demonstrate the effectiveness of the proposed method.

Movement Pattern Analysis Based on Sequence Signatures

Increased affordability and deployment of advanced tracking technologies have led researchers from various domains to analyze the resulting spatio-temporal movement data sets for the purpose of knowledge discovery. Two different approaches can be considered in the analysis of moving objects: quantitative analysis and qualitative analysis. This research focuses on the latter and uses the qualitative trajectory calculus (QTC), a type of calculus that represents qualitative data on moving point objects (MPOs), and establishes a framework to analyze the relative movement of multiple MPOs. A visualization technique called sequence signature (SESI) is used, which enables to map QTC patterns in a 2D indexed rasterized space in order to evaluate the similarity of relative movement patterns of multiple MPOs. The applicability of the proposed methodology is illustrated by means of two practical examples of interacting MPOs: cars on a highway and body parts of a samba dancer. The results show that the proposed method can be effectively used to analyze interactions of multiple MPOs in different domains.