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  • Open Access

    ARTICLE

    Intelligent Urban Transportation over Complex Vehicle Networks with YOLOv8 for Traffic Flow Monitoring

    Mohammed Alonazi1, Muhammad Adeel Ahmed Tahir2, Adnan Ahmed Rafique2, Maha Abdelhaq3, Raed Alsaqour4, Ahmad Jalal5,6, Jeongmin Park7,*

    CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086550 - 15 September 2026

    Abstract Accurate vehicle detection, tracking, and counting are fundamental components of Intelligent Transportation Systems (ITS) and urban traffic surveillance. However, real-world deployment remains challenging due to domain shifts, illumination variations, occlusions, dense traffic conditions, and heterogeneous data distributions. Existing studies often address detection, tracking, and counting as independent tasks, resulting in limited cross-domain generalization and inconsistent performance in complex traffic environments. To overcome these limitations, this paper proposes a unified cross-domain framework that jointly integrates vehicle detection, tracking, and lane-aware counting within a single intelligent traffic analytics pipeline. The proposed framework begins with image enhancement using… More >

  • Open Access

    ARTICLE

    Adaptive Correlation Filter Learning with Motion Smoothing for UAV Tracking

    Yu-Feng Yu1,*, Xiaoying Tan1, Qirong Wu1, Guoxia Xu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.085413 - 28 August 2026

    Abstract To tackle critical visual tracking difficulties arising in UAV tracking tasks, including frequent target occlusion and abrupt fast motion during high-altitude inspection, we propose an adaptive correlation filter tracking algorithm incorporating a motion smoothing module and adaptive residual regularization, named MACF. The tracker is constructed via multi-strategy fusion of two elaborately designed components at the algorithmic modeling level. First, we design a Motion Smoothing Module (MSM) that conducts weighted fusion of historical motion trends in the modeling pipeline. It suppresses search window jitter arising from instantaneous positioning errors and lowers target drift risk by providing More >

  • Open Access

    ARTICLE

    Contact Force Tracking in Robotics Using Reference-Dependent Constant Impedance Control

    Abubaker Ahmed1, Hosham Wahballa2,*, AlaEldin Awouda3, Arafat Abdulgader Mohammed Elhag4, Ahmed Hamza Osman5, Mubarak Himmat6

    CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.084395 - 28 August 2026

    Abstract Accurate force regulation is essential in robotic contact tasks such as polishing, grinding, and assembly. However, conventional impedance controllers often exhibit limited force-tracking accuracy, while adaptive methods require high tuning effort and computational cost. To address these issues, this paper proposes a Constant Impedance Force Controller (CIFC) based on a Force Reference Dependent Impedance (FRDI) model, which is developed and validated through computer modeling and simulation. Robot environment interaction is computationally modeled as a mass damper spring system, and a position-based impedance framework is employed to regulate force deviations. A compensation signal derived from the FRDIMore >

  • Open Access

    REVIEW

    Optimization of Photovoltaic Systems via AI-Based Solar Tracking and MPPT: Trends, Challenges, and Bibliometric Insights

    Hamza Rafik1, Oussama Khouili2, Mohamed Louzazni1, Petru Adrian Cotfas3, Daniel Tudor Cotfas3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.084256 - 28 August 2026

    Abstract The rapid expansion of photovoltaic (PV) technologies has necessitated the enhancement of energy conversion efficiency by developing more and more sophisticated control and optimization techniques. In particular, novel MPPT methods combined with solar tracking systems and AI approaches emerge as a promising solution to surmount the barriers of the conventional PV systems. This research presents a critical assessment of the recent developments in the research area of PV systems with MPPT algorithms, solar tracking mechanisms, and AI-based techniques. Therefore, papers with publication years from 2021 to 2025 were selected using Web of Science Core Collection. More >

  • Open Access

    ARTICLE

    Reflective Fiber Optic Angle Sensor for Monitoring the Rotation State of Monopolar Photovoltaic Tracking Mounts

    Qingmin Hou1, Guanghua Xiao1, Tongtong Dai2,*

    Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.087157 - 24 August 2026

    Abstract To address the issue of angular deviation in inclined single-axis photovoltaic tracking mounts during long-term operation-caused by wind disturbances, mechanical transmission gaps, installation inaccuracies, and environmental factors-a angle sensor based on reflective fiber-optic ranging principles has been developed for monitoring the rotation angle of the main shaft. This sensor employs a structural conversion approach of “using straight lines to replace curves”, transforming the shaft’s rotational angle into linear displacement of a mirror via a gear-rack mechanism, and generating corresponding output voltage signals through variations in reflected light intensity to measure rotation angles. Due to factors… More >

  • Open Access

    ARTICLE

    V2X-Enabled Parameter-Estimation-Based ILC for Repetitive Trajectory Tracking of Connected Vehicles under Trial-Varying Conditions

    Ping Ma1,2, Quan Wang1,2, Yiyang Chen3,*

    CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084488 - 13 August 2026

    Abstract Connected vehicles operating in V2X-enabled intelligent transportation systems often perform repetitive trajectory tracking in repeated tasks. In practical applications, traffic conditions, communication quality, and sensing accuracy may vary from trial to trial. These variations induce time-varying dynamics across repeated runs and reduce the effectiveness of iterative learning control (ILC) schemes when fixed or inaccurately identified models are used. To address this issue, this paper proposes a parameter-estimation-based ILC framework for connected vehicles. Parameter estimation is integrated with a norm-optimal ILC design through an expectation-maximization strategy. The time-varying model parameters and the learning input are updated More >

  • Open Access

    ARTICLE

    Real-Time Video Target Tracking via Geometric Coordinate Mapping

    Na Li1, Yashu Zhang1, Fengpu Lin1, Liutao Zhao2,*, Zhongshan Zhu3, Chen Tom4, Tengfei Tu5

    CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.083412 - 23 July 2026

    Abstract Accurate mapping of video imagery to physical space coordinates represents a fundamental challenge in dynamic target tracking and intelligent video analysis systems. Traditional methods struggle to maintain stable coordinate mapping in real-time video streams due to imaging distortion variations and changing environmental conditions. This paper presents a real-time coordinate mapping approach that integrates geometric constraints with online distortion correction to achieve stable pixel-to-target coordinate transformation for video target tracking applications. The proposed method introduces a planar geometric consistency constraint and an online distortion parameter update mechanism within a unified optimization framework, enabling adaptive adjustment of… More >

  • Open Access

    ARTICLE

    An Adaptive Trajectory-Assisted Dynamic Indoor Positioning Method Based on RSS Fingerprinting

    Jing Liu1,2, Weijie Tan1,2,3,*

    CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.083401 - 23 July 2026

    Abstract Due to its low hardware cost and ease of deployment, WiFi fingerprinting has become a prominent research direction in indoor positioning. However, traditional methods based on Received Signal Strength (RSS) still face three critical challenges: susceptibility to noise interference, low retrieval efficiency as fingerprint databases scale up, and trajectory instability in dynamic environments. These challenges are inherently rooted in the stochastic fluctuation of RSS signals, the high-dimensional and non-Euclidean nature of fingerprint space, and the unpredictability of user movement patterns. To address these limitations, an adaptive trajectory-assisted dynamic indoor positioning algorithm based on RSS fingerprinting,… More >

  • Open Access

    ARTICLE

    KBGWO-RNP: Knowledge-Based Grey Wolf Optimizer for Multi-Criteria RFID Network Planning in Medical Asset Monitoring

    Mohamad Khairi Ishak1, Samir Ait Lhadj Lamin2,3, Mohammad Shokouhifar4,*, Aseel Smerat5, Kamal M. Othman6, Abdulfattah Noorwali6, Esam Y.O. Zafar6

    CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.078029 - 23 July 2026

    Abstract Radio Frequency Identification (RFID) has emerged as an effective remote technology for real-time monitoring and management of medical assets in hospitals. Most existing RFID Network Planning (RNP) methods are primarily based on either heuristic or metaheuristic approaches. While heuristic approaches are computationally efficient and converge rapidly, they often suffer from premature convergence and suboptimal network configurations. Conversely, metaheuristic algorithms provide stronger global search capabilities and improved solution quality, but they typically require higher computational effort and may still exhibit stagnation in local optima when applied to complex hospital layouts. To overcome these limitations while utilizing… More >

  • Open Access

    ARTICLE

    TopoEKF: From State-Space Estimation to Topological Signatures for Enhanced Multi-Object Tracking and Anomaly Detection in UAVs

    Rabia Kıratlı1, Hatice Ünlü Eroğlu2, Alperen Eroğlu1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.081411 - 30 June 2026

    Abstract Reliable multi-object detection and tracking play a critical role in Unmanned Aerial Vehicles-based aerial surveillance applications operating under challenging real-world conditions. This study presents a mathematically grounded, model-driven tracking framework named TopoEKF, which integrates an enhanced Adaptive Extended Kalman Filter with Topological Data Analysis to improve both tracking robustness and anomaly detection performance. Unlike prior approaches that primarily focus on refining object detection architectures, this work emphasizes the predictive power of iterative Bayesian filtering, optimal state estimation, and adaptive error minimization within a unified mathematical framework. The proposed system employs a carefully optimized YOLOv12 detector… More >

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