Tracking System Research Articles

Tally Tracking System

In today’s fast-paced world, effectively managing personal expenses is crucial for maintaining financial stability and achieving long-term goals. However, many existing systems lack a user-friendly interface to efficiently track and categorize expenses. Users often struggle to enter expense details manually and visualize their spending trends over time. These limitations can make it difficult to identify spending patterns and create effective financial plans. Without proper categorization and reporting features, users may fail to track their expenses accurately, which leads to poor financial decisions. To overcome these drawbacks, the new system features a modern, user-friendly website built using Python and Flask. This system allows users to easily enter their expense details, including the category of the expense, such as food, entertainment, transportation, or utilities. The website is designed to ensure that users can quickly input their daily expenses, making it more accessible and intuitive. With Flask as the backend framework, the system ensures efficient processing of user data and seamless integration of the front-The end interface provides a smooth experience for users who are not necessarily tech-savvy. One of the key features of the proposed system is its ability to visualize the entered data in various formats, allowing users to view their expenses on a day-by- day, month-by-month, or year-by-year basis. The system uses interactive graphs and charts to display data, making it easy for users to track their spending patterns over time. In addition, users can generate detailed reports based on their selected timeframe, which provides insights into their financial habits and helps facilitate better decision-making. This solution empowers users to take control of their finances by providing a clear, graphic representation of their expenses and an easy way to generate periodic reports, thereby enhancingoth their financial planning and awareness.

A novel approach to sustainable behavior enhancement through AI-driven carbon footprint assessment and real-time analytics

This research introduces an Artificial Intelligence-driven mobile application designed to help users calculate and reduce their Carbon Footprint (CFP). The proposed system employs an Intelligent Sustainable Behavior Tracking and Recommendation System, analyzing users' carbon emissions from daily activities and suggesting eco-friendly alternatives. It facilitates sustainability discussions through its chat community and educates users on sustainable practices via an intelligent chatbot powered by a sustainability knowledge base. To promote social engagement around sustainability, the application incorporates a competition and reward system. Additionally, it aggregates behavioral data to inform government sustainability policies and address challenges. Emphasizing individual responsibility, the proposed system stands out from other systems by offering a comprehensive solution that integrates recommendation, education, monitoring, and community engagement, contributing to the cultivation of sustainable communities. The results of a user study (n = 10) employing paired sample t-tests across the three dimensions of the Theory of Reasoned Action (TRA) revealed varying effects of using the application on attitudes, subjective norms, and behavioral intentions related to promoting sustainable human behavior. While the application did not yield significant changes in attitudes (t (9) = 1.7, p = 0.123), or behavioral intentions (t (9) = 0.6, p = 0.541), it did produce a significant increase in subjective norms (t (9) = 4.2, p = 0.002). This suggests that while attitudes towards using this application for sustainability and behavioral intentions remained relatively stable, there was a notable impact on the perception of social influence to engage in sustainable behavior through the use of the application attributed to the sustainability reward system.

DELIVERY TRACKING SYSTEM WITH ON-DEMAND LOCATION UPDATE DI PT ANUGRAH HADI ELECTRIC MENGGUNAKAN METODE AGILE

PT Anugrah Hadi Electric, an electrical general supplier in Tangerang, faces challenges in the process of delivering goods to customers in the Jabodetabek area. The company still relies on conventional delivery methods where the owner directly delivers the goods, which causes constraints in time efficiency and communication with customers. This research aims to develop a delivery tracking system with on-demand location update feature to improve operational efficiency and customer satisfaction. Using Agile methodology, the system is developed by integrating Firebase technology for real-time location tracking, Kotlin for mobile application development, Laravel as the backend framework, and MySQL as the database. The system allows customers to monitor delivery status directly through the application, reducing the need for manual communication with the owner. The implementation results show significant improvements in delivery efficiency and customer satisfaction. The system successfully reduces the communication burden on the owner and provides better transparency to customers regarding the status of their shipments. For further development, the addition of automatic notification features, improved data security, and integration with digital payment systems are recommended. Periodic evaluation of the application's performance is also needed to ensure the system continues to meet the needs of the company and customers along with technological developments.

Sequential fusion estimation for nonlinear systems under deceptive attacks

AbstractThis article deals with sequential fusion estimation for nonlinear systems under deceptive attacks, which may happen during transmissions of measurements and system states over communication networks. The estimator is developed by incorporating measurement fusion and local estimate fusion with attack detection. Moreover, a compensation strategy is designed to mitigate the impact of deceptive attacks on performance degradation. The proposed method may preserve the data integrity for accurate state estimation with deceptive attacks. Numerical simulation with the target tracking systems verifies the effectiveness of the proposed method.

Migratory movements of bats are shaped by barrier effects, sex-biased timing and the adaptive use of winds

BackgroundMigratory bats perform seasonal movements between their summer and winter areas. When crossing ecological barriers, like the open sea, they are exposed to an increased mortality risk due to energetically demanding long-distance flights and unexpected inclement weather events. How such barriers affect bat migratory movements is still poorly known.MethodsTo study bat migration patterns in response to an ecological barrier, we tagged 44 Nathusius’ pipistrelles Pipistrellus nathusii with radio-transmitters on the East coast of the United Kingdom (UK) in spring 2021 and 2022. Subsequently, we assessed their movements to continental Europe using the MOTUS Wildlife Tracking System. We investigated route selection, timing of migration, overall migration speed and the influence of wind on airspeed, groundspeed and flight altitude during migratory overseas flights.ResultsBarrier effects cause migratory movements along the coast, and crossings over sea are shortened by deviating from the general migration direction. Males depart from the UK later in the season compared to females. The overall migration speed of females was 61 km/day and 88 km/day after their last detection in the UK. Our estimated airspeeds during oversea flights correspond well with airspeeds measured in a wind tunnel. Bats use wind adaptively to reduce airspeed when flying under tailwind and increase airspeed when flying under crosswind conditions. Departures over sea coincidence with tailwinds, enabling bats to more than double their airspeed, reaching ground speeds of up to 16.8 m/s (60.5 km/h). Our analysis suggests that bats select altitudes with favourable wind conditions and that they seek altitudes of several hundred meters, possibly extending up to 2,500 m. Low-altitude migration occurs when wind conditions are less favourable.ConclusionsOur study demonstrates that bat migratory movements are highly influenced by barrier effects, sex-biased timing of migration and the adaptive use of winds. The results of our study contribute to a more comprehensive understanding of the decision-making process and adaptations bats employ during their migration. Elucidating bat migration patterns will enable us to develop effective conservation measures, for example in relation to the development and operation of coastal and offshore wind farms.

Identification Method for Railway Rail Corrugation Utilizing CEEMDAN-PE-SPWVD

Rail corrugation intensifies wheel–rail vibrations, often leading to damage in vehicle–track system components within affected sections. This paper proposes a novel method for identifying rail corrugation, which combines Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), permutation entropy (PE), and Smoothed Pseudo Wigner–Ville Distribution (SPWVD). Initially, vertical acceleration data from the axle box are decomposed using CEEMDAN to extract intrinsic mode functions (IMFs) with distinct frequencies. PE is used to evaluate the randomness of each IMF component, discarding those with high permutation entropy values. Subsequently, correlation analysis is performed on the retained IMFs to identify the component most strongly correlated with the original signal. The selected component is subjected to SPWVD time–frequency analysis to identify the location and wavelength of the corrugation occurrence. Filtering is applied to the IMF based on the frequency concentration observed in the time–frequency analysis results. Then, frequency–domain integration is performed to estimate the rail’s corrugation depth. Finally, the algorithm is validated and analyzed using both simulated data and measured data. Validation results show that this approach reliably identifies the wavelength and depth characteristics of rail corrugation. Additionally, the time–frequency analysis results reveal variations in the severity of corrugation damage at different locations.

Coded Bias in Applicant Tracking Systems

Coded Bias in Applicant Tracking Systems

Enhanced Space Debris Detection and Monitoring Using a Hybrid Bi-LSTM-CNN and Bayesian Optimization

Space debris detection is important to the integrity of space missions and satellites, especially with the increase in the number of satellites and spacecraft in orbit. This paper addresses this by a new concept innovative approach using hybrid Bi-LSTM-CNN architecture which is optimized using Bayesian Optimization. The study presents an analysis approach based on the whole combination of machine learning and deep learning, a high-quality space debris detector, that can identify both the kind of object and the size of its RCS. The new method goes beyond what we have done so far and shows better results on a wide range of evaluation parameters, such as accuracy, precision, memory, and F1 score. Also, the study takes up the pragmatic issue of training time, thereby ensuring performance in real time. Esthetic trials on real datasets confirm the fit of the hybrid model, sensitivity, and efficacy with 99.16% and 99.98% detection and prediction of space debris types, respectively. In summary, this paper makes space debris tracking much more robust and mitigates threats associated with spaceflight and satellite operations, but they can offer a lot of information on threats and mitigation measures. The findings suggest that this hybrid model could be augmented with current space debris tracking systems, to increase their predictive power and operational effectiveness. Received: 2 July 2024 | Revised: 15 August 2024 | Accepted: 6 September 2024 Conflicts of Interest The author declares that she has no conflicts of interest to this work. Data Availability Statement The datasets cited in this manuscript are publicly available and can be accessed from the original sources referenced in the text. The data that support the findings of this study are openly available in Kaggle at https://www.kaggle.com/datasets/kandhalkhandeka/sate llites-and-debris-in-earths-orbit/data. No additional data were generated or analyzed during the current study Author Contribution Statement Ishaani Priyadarshini: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition.

Hybrid Artificial-Intelligence-Based System for Unmanned Aerial Vehicle Detection, Localization, and Tracking Using Software-Defined Radio and Computer Vision Techniques

The proliferation of drones in civilian environments has raised growing concerns about their misuse, highlighting the need to develop efficient detection systems to protect public and private spaces. This article presents a hybrid approach for UAV detection that combines two artificial-intelligence-based methods to improve system accuracy. The first method uses a software-defined radio (SDR) to analyze the radio spectrum, employing autoencoders to detect drone control signals and identify the presence of these devices. The second method is a computer vision module consisting of fixed cameras and a PTZ camera, which uses the YOLOv10 object detection algorithm to identify UAVs in real time from video sequences. Additionally, this module integrates a localization and tracking algorithm, allowing the tracking of the intruding UAV’s position. Experimental results demonstrate high detection accuracy, a significant reduction in false positives for both methods, and remarkable effectiveness in UAV localization and tracking with the PTZ camera. These findings position the proposed system as a promising solution for security applications.

A novel architecture for the detection, exploitation and historical archival of indoor semantic trajectories: a case study on nursing homes

Purpose This paper aims to build an indoor positioning system capable of tracking residents and caregivers and feeding a novel information system with this data. This information system introduces three main interesting modules: a compact data structure to efficiently store the gathered data, an activity deduction module that add semantics to the raw captured trajectories and a user-friendly interface able to display this spatio-temporal information. Design/methodology/approach Their proposal was built following an iterative and incremental development. Nursing home managers cooperated in the requirement composition phase, while some residents and caregivers contributed testing the system with their real trajectories. Findings Their contribution is a functional information system that can evaluate the quality of healthcare provided to residents and assess the efficiency of the nursing home as a business. This information system includes a novel state-of-the-art compact data structure to efficiently work with the captured data. Originality/value A new system has been designed and implemented using a wide range of technologies to support the necessities of a real enterprise. The rudimentary position tracking systems were upgraded to a feasible automatic indoor positioning solution. The amount of information generated by this new strategy is dealt with compact data structures, reducing space usage without jeopardizing query times. Those compressed positions are tagged with semantic information that enables individual activity analysis. Last, a user-friendly interface lets the final user interact with the gathered and calculated information. As future work, the authors plan to improve the integration of this new information system with other systems already in use in indoor mobile workforce environments.

A STAND-ALONE HYBRID POWER SYSTEM BASED ON PV ENERGY AND HYDROGEN FUEL CELLS WITH ENERGY STORAGE SYSTEMS

This article is focused on the construction of a stand-alone residential 5-kW hybrid power system to feed different domestic loads at a typical house in Thi-Qar City, Iraq, including lighting loads, Table fan, Smartphone charger, TV, Microwave and Cooler. The stand-alone residential 5-kW hybrid power system consists of PV generator, PEMFC, storage batteries, Electrolyzer and hydrogen tank. The battery and hydrogen subsystem, composed of a fuel cell (FC), electrolyzer, and hydrogen storage tank, act as energy storage and support systems. The research in steps includes the design of the hybrid system. A program has been used in MATLAB to size system components in order to match the load of the site in the most cost-effective way. Evaluation of the economic feasibility of the same hybrid system when using a solar tracking system for photovoltaic cells. The simulation results demonstrate the hybrid system's ability to supply the required electrical energy to the loads, as well as the increase in hydrogen production when using the solar tracking system, which makes it possible to store excess hydrogen in the long term for later use when the photovoltaic energy decreases according to the seasons of the year.

Full-Scale Assessment of the “5GT System” for Tracking and Monitoring of Multimodal Dry Containers

A novel tracking and monitoring system for ISO 668 dry containers was realized by the ESA-funded “5G SENSOR@SEA” project, integrating 5G cellular technologies for massive Internet of Things with a GEO satellite-optimized backhauling link. The scope is the development of monitoring and tracking new services for multimodal container shipping. With the cooperation of four industrial partners and a telecommunication research center, the so-called “5GT System” was designed, developed, tested and validated up to field trials. Several modules of the system were designed, built and finally installed on the ship and in the teleport: the container tracking devices placed on the containers, the NB-IoT cellular network with optimized satellite backhauling, the Ku-band satellite terminals and the maritime service platform based on the OneM2M standard. The field trial conducted during the intercontinental liner voyage of a container ship showed primary technical achievements, including fair switching between terrestrial and satellite networks, reduction in packet loss in the open sea scenario and seamless integration of the BLE mesh network over the container tracking devices as NB-IoT/BLE LE Mesh gateways.

Optimizing dormant account management in UAE banking: Legal gaps and proposed reforms

The management of dormant accounts and unclaimed balances is a pressing challenge in the banking sector of the United Arab Emirates (UAE), particularly given the complex regulatory landscape. This study analyzes 150 dormant accounts across five major UAE banks (Emirates NBD, First Abu Dhabi Bank, Dubai Islamic Bank, Sharjah Islamic Bank, and Abu Dhabi Commercial Bank) and identifies gaps in the legal framework, including the absence of clear definitions and handling of non-monetary assets.The study investigates the legal framework governing dormant accounts, specifically focusing on the Dormant Accounts System No. 1 of 2020. The results highlight critical issues, including the lack of clear timelines for transferring unclaimed balances and inconsistencies in communication protocols for notifying account holders. Furthermore, the study emphasizes the need for standardized practices across financial institutions in the UAE.To address these challenges, the study proposes legislative amendments to improve asset management and consumer protection. Key recommendations include establishing standardized definitions, implementing automated tracking systems for dormant accounts, and integrating dormant balances into social welfare programs to enhance public trust. These reforms could significantly improve operational efficiency and legal clarity in the UAE banking sector, contributing to a more transparent and effective management of dormant accounts and unclaimed balances. Acknowledgments The authors are thankful to the Deanship of Graduate Studies and Scientific Research at the University of Bisha for supporting this work through the Fast-Track Research Support Program.

Design and Assessment of a Linear Drive‐Controlled Tilt‐Roll Heliostat with Sun Tracking Algorithm for Small‐Scale Solar Installation

Heliostats are devices used for solar concentration that use mirrors oriented according to the position of the sun. A heliostat's main function is to redirect sunlight for use in a variety of applications, including heating, lighting, scientific research, and solar power generation. The two‐axis tracking employed in the device ensures that the reflected irradiance is aimed at a predetermined target. The design and evaluation of a tilt‐roll two‐axis tracking heliostat are presented in this article. The model consists of a mirror 0.45 m in width and 0.45 m in length installed on a pedestal of height 0.75 m. The motion of the heliostat is controlled using two separate linear drives via a sun‐tracking algorithm implemented in a microcontroller. A small‐scale tilt‐roll design with a reflective area (mirror) of 0.2025 m2 is established. This novel design eliminates the need for commercially available solar tracking systems and can be deployed in areas of limited installation space. Dual‐axis heliostat design used here provides an effective way to track the sun's movement for maximum solar energy capture by combining tilt and roll mechanisms. This design ensures tracking precision for optimal solar energy concentration making it well‐suited for experimental and smaller‐scale deployments.

Temperature-Related Variations in Physical Performance During Elite Soccer Matches

The aim of this study was to examine the differences in match running performance (MRP) according to the ambient temperature during UEFA Champions League (UCL) matches. Data were collected using an optical tracking system from all teams (n = 32) in all UCL matches (n = 125) during the 2022/23 season, and classified according to the ambient temperature at which matches were played: <5 °C, 6–10 °C, 11–20 °C, and >21 °C. The results revealed the following: (i) less total distance was covered in matches played at ≥21 °C compared to the matches played at 6–10 °C (d = 0.58), (ii) less high-speed running and high-intensity running were covered in matches played at ≥21 °C compared to the matches played at 11–20 °C (d = 0.54 and 0.43, respectively), 6–10 °C (d = 0.89 and 0.8, respectively), and ≤5 °C (d = 0.62 and 0.57, respectively), and (iii) less sprinting was covered in matches played at ≥21 °C compared to the matches played at 6–10 °C (d = 0.22). These findings indicated the significant differences in MRP when UCL matches were played at different ambient temperatures, with notable reductions in overall and high-intensity efforts in warmer conditions.

Assessment of proprioceptive and kinesthetic memory in shoulder joint using KEMTAI software system

<p style="text-align: justify;">Proprioception and kinesthesia refer to the sense of joint position and movement, assessable through joint position sense (JPS). We evaluated the potential of the KEMTAI software system in tracking and quantifying shoulder movement by examining 40 subjects (ages 22-68) divided into three age groups. Subjects, blindfolded, performed shoulder flexion, stopped on voice command and by their own at predefined angles measured by the software. Our findings indicated no significant differences in JPS accuracy across age groups, although precision improved with external cues, and a decline in JPS memory over short intervals was observed, suggesting further exploration is needed.</p>

Synthesis of synchronous filter for target tracking system of the self-guided infrared flying vehicle

This article deals with research in the field of noise-based signal processing for target tracking systems of the self-guided infrared flying vehicle. The article conducts theoretical analysis, builds block diagrams, structural diagrams and describes the operating principle of the synchronous filter in low and high input frequency, and proposes a mathematical model of this filter. The simulation results, carried out in Matlab/Simulink and Atium environments, are the basis for designing the synchronous filter electrical circuit of the correction circuit board attached to the launch mechanism of the self-guided infrared flying vehicle.

Edge Based Intelligent Secured Vehicle Filtering and Tracking System Using YOLO and EasyOCR

Edge Based Intelligent Secured Vehicle Filtering and Tracking System Using YOLO and EasyOCR

Automated Transport Management System: Route Optimization and Attendance Tracking for Institutions

Educational institutions face significant challenges in managing student transportation, such as inefficient route planning, manual attendance tracking, and the lack of real-time communication. These issues contribute to delays, operational inefficiencies, and safety concerns, leaving students, parents, and administrators with limited access to critical information about transportation logistics. Existing literature highlights advancements in transportation management through IoT, RFID, GPS, and AI, revealing both the potential of these technologies and their limitations in addressing hardware dependencies, network constraints, and manual interventions. Notable research includes IoT-based systems for bus tracking and attendance, Wi-Fi-enabled attendance solutions, and multiagent routing optimization algorithms, which underscore the effectiveness of real-time tracking and automation but reveal gaps in scalability, cost-effectiveness, and hardware reliability. To bridge these gaps, this project introduces the Automated Transport Management System (ATMS), a comprehensive platform designed to enhance efficiency, safety, and communication in student transportation. ATMS integrates GPS for real-time route visualization, barcode-based automated attendance logging, and proactive notifications accessible through a user-friendly web interface. This approach minimizes manual errors, reduces wait times, and ensures reliable service even in areas with variable connectivity, providing an efficient and flexible solution for educational institutions. By continuously evolving its features, ATMS aims to establish a new standard in transportation management, promoting student safety and operational effectiveness.

Comparative Study of Linear Control Strategies for Regulation, Tracking of Unstable Systems and the Scope for LQR Infusion in Optimisation Problems

Comparative Study of Linear Control Strategies for Regulation, Tracking of Unstable Systems and the Scope for LQR Infusion in Optimisation Problems