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A comprehensive analysis of real-time video anomaly detection methods for human and vehicular movement

Multimedia Tools and Applications 2025年第10期84卷 7519-7564页

作者： Pathirannahalage, Iroshan Jayasooriya, Vidura Samarabandu, Jagath Subasinghe, Akila Department of Electrical and Electronic Engineering Faculty of Engineering University of Sri Jayewardenepura Gangodawila Nugegoda10250 Sri Lanka Department of Electrical and Computer Engineering Faculty of Engineering Western University LondonONN6A 3K7 Canada

The ubiquitous integration of computer vision technologies has revolutionised various application domains, ranging from agriculture and transportation to healthcare and the military. In this context, real-time anomaly detection in video streams has emerged as a critical facet, particularly concerning the movement of vehicles and humans. Despite the increasing adoption of these technologies in real-life applications, a conspicuous research gap exists, the necessity for robust validation of benchmarked datasets and state-of-the-art methods before deployment in real-time settings. This paper addresses this gap through a holistic approach to extensively review the real-time video anomaly detection literature in Human and Vehicular Movement applications. Specifically, we examine the various architectures used for real-time video anomaly detection and provide a detailed analysis of their performance on benchmarked datasets. Furthermore, we delve into the multifaceted challenges encountered when identifying anomalies across different categories, encompassing issues related to computational resources, noise interference, frame complexity, data sparsity, diversity, ethical considerations and their combinations. We address these challenges by proposing potential future trends in anomaly detection, including the development of more sophisticated datasets, exploration of hybrid architectural models, integration of multi-camera systems, advancement in open-set action recognition algorithms, model development for cutting-edge process automation systems, harnessing the potential of IoT, leveraging edge computing, and incorporating drone technologies into anomaly detection strategies. This paper aims to illuminate the direction of real-time anomaly detection for future research in vehicular and human movement. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Anomaly detection

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Hybrid robust fault detection and isolation of satellite reaction wheel actuators

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Journal of Control and Decision 2024年第1期11卷 117-131页

作者： H.Abbasi Nozari S.J.Sadati Rostami Paolo Castaldi Silvio Simani Faculty of Electrical and Computer Engineering Babol Noshirvani University of TechnologyBabolIran Department of Electrical Electronic and Information EngineeringUniversity of BolognaCesenaItaly Department of Engineering University of FerraraFerraraItaly

In this paper,a combined robust fault detection and isolation scheme is studied for satellite system subject to actuator faults,external disturbances,and parametric *** proposed methodology incorporates a residual generation module,including a bank of filters,into an intelligent residual evaluation ***,residual filters are designed based on an improved nonlinear differential algebraic approach so that they are not affected by external *** residual evaluation module is developed based on the suggested series and parallel ***,a new ensemble classification scheme defined as blended learning integrates heterogeneous classifiers to enhance the performance.A wide range of simulations is carried out in a high-fidelity satellite simulator subject to the constant and time-varying actuator faults in the presence of disturbances,manoeuvres,uncertainties,and *** obtained results demonstrate the effectiveness of the proposed robust fault detection and isolation method compared to the traditional nonlinear differential algebraic approach.

关键词： Robust fault detection and isolation reaction wheels blended learning series and parallel fault detection and isolation forms satellite attitude control system

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Grid-Interactive Novel Resilient Control of Solar PVWind-Battery Storage Microgrid Under Distorted and Unbalanced Grid Voltages

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IEEE Transactions on Consumer Electronics 2025年第1期71卷 1744-1757页

作者： Gali, Vijayakumar Jamwal, Prashant Kumar Gupta, Nitin Babu, B. Chitti Ahmadi, Mohammad Jawid Morey, Meghraj Sudhakar University of Hertfordshire School of Physics Engineering and Computer Science Department of Electrical and Electronics Engineering HatfieldAL109AB United Kingdom Nazarbayev University Department of Electrical and Computer Engineering Astana Kazakhstan Malaviya National Institute of Technology Department of Electrical Engineering Jaipur India Indian Institute of Information Technology Design and Manufacturing Department of Electronics and Communication Kancheepuram India

Integrating solar photovoltaic (PV), wind, and battery storage (BS) systems into the grid introduces significant power quality (PQ) challenges. In particular, the intermittent nature of solar PV and wind energy systems (WES), combined with nonlinear loads, can lead to grid instability. As a result, maintaining a reliable and high-quality power supply to consumers becomes a substantial challenge. This article presents two novel solutions to address these challenges: the anti-windup mixed-order generalized integrator (AWMOGI) and the adaptive delay operation period filter (ADOPF). The AWMOGI effectively extracts fundamental components from distorted utility grid voltages, minimizing DC offset and reducing steady-state oscillations. Meanwhile, the ADOPF swiftly captures positive sequence voltage components by introducing a two-sampling-interval delay in the d-q coordinate system. The hierarchical-loop controller parameters are optimized using a customized Harris Hawks Optimization (HHO) algorithm, which enhances error reduction and facilitates rapid establishment of reference values for DC-link voltage loop control. An adaptive dynamic power management scheme also enables the microgrid (MG) to manage surplus power from MG sources, reducing stress on the BS and ensuring DC-link voltage stability. The experimental results demonstrate significant improvements in handling utility grid abnormalities, dynamic loads, and intermittent microgrid source operation. The experimental results show a zero DC-off set and steady-state errors, a fast computational time of 35e-5s, and the THD of grid currents of 3.16%, which complies with the IEEE 519 standards. © 1975-2011 IEEE.

关键词： Adaptive filters

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Adaptive algorithm for controlling the power management system on offshore jack-up drilling rigs

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Energy Sources, Part A: Recovery, Utilization and Environmental Effects 2024年第1期46卷 16717-16737页

作者： Cemeljic, Hrvoje Havelka, Juraj Jeremic, Aleksandar Kuzle, Igor Department of Energy and Power Systems Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Department of Electrical & Computer Engineering McMaster School of Biomedical Engineering McMaster University HamiltonON Canada Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

The power systems of offshore jack-up drilling rigs consist of diesel generators running in parallel load-sharing mode, controlled by an automatic Power Management System (PMS). In this paper, the operational performance of the diesel generators (DG) and the PMS on a jack-up drilling rig is investigated, focusing on two critical offshore drilling operations: "pipe tripping" and "pulling/pumping out of the hole" (POOH). During these operations, large power swings occur in the system, subjecting the DGs to sudden load surges. These severe imbalances in the system cause the PMS to intermittently start and stop the engines throughout the operation, leading to various problematic conditions in the power plant. The paper provides a novel solution for intermittent starting and stopping of the DGs in the form of development and implementation of an adaptive PMS algorithm, a mathematical model of the system and a machine learning approach to event prediction of PMS operation in offshore drilling. Research demonstrates a noteworthy decrease in intermittent DG starting and stopping when the adaptive algorithm is implemented, with a 96% reduction during pipe tripping and an 87% reduction during POOH. This improvement comes at the expense of an 11% increase in engine running hours and a 1.5% rise in fuel consumption. Furthermore, by configuring the adaptive algorithm to economy mode, savings of up to 1700 liters of fuel per month are achievable. © 2024 Taylor & Francis Group, LLC.

关键词： Adaptive algorithms

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Continuous Query-based Data Trading

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Performance Evaluation Review 2024年第1期52卷 73-74页

作者： Cheng, Jin Ding, Ningning Lui, John C.S. Huang, Jianwei School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Shenzhen Shenzhen China Department of Electrical and Computer Engineering Northwestern University Evanston United States Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Hong Kong

In the era of big data, traditional data trading methods designed for one-time queries on static databases fail to meet the demands of continuous query-based trading on streaming data, often resulting in repeated and inaccurate charges due to neglecting computation sharing in continuous query execution. To address this, we introduce CQTrade, the first trading framework tailored for continuous queries, which incorporates computation sharing across different time windows and queries, enhancing integration with existing trading systems. Our contributions include a theoretical analysis of computation-sharing techniques, the development of a general optimization problem to maximize seller revenue adaptable to various techniques, and the proposal of a branch-and-price algorithm to handle the problem's complexity. Our evaluation shows that the proposed framework improves the success rate of data trading by 12.8% and boosts the seller's revenue by an average of 28.7%, compared to the one-time query-based data trading methods used in the current data market. © 2024 Owner/Author.

关键词： Integer programming

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Single-ended Fault Detection Scheme Using Support Vector Machine for Multi-terminal Direct Current Systems Based on Modular Multilevel Converter

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Journal of Modern Power Systems and Clean Energy 2023年第3期11卷 990-1000页

作者： Guangyang Zhou Xiahui Zhang Minxiao Han Shaahin Filizadeh Zhi Geng School of Electrical and Electronic Engineering North China Electric Power UniversityBeijing 102206China Department of Electrical and Computer Engineering University of ManitobaWinnipegCanada

This paper proposes a single-ended fault detection scheme for long transmission lines using support vector machine(SVM)for multi-terminal direct current systems based on modular multilevel converter(MMC-MTDC).The scheme overcomes existing detection difficulties in the protection of long transmission lines resulting from high grounding resistance and attenuation,and also avoids the sophisticated process of threshold value *** high-frequency components in the measured voltage extracted by a wavelet transform and the amplitude of the zero-mode set of the positive-sequence voltage are the inputs to a trained *** output of the SVM determines the fault type.A model of a four-terminal DC power grid with overhead transmission lines is built in PSCAD/*** results of EMTDC confirm that the proposed scheme achieves 100%accuracy in detecting short-circuit faults with high resistance on long transmission *** proposed scheme eliminates mal-operation of DC circuit breakers when faced with power order changes or AC-side *** robustness and time delay are also assessed and shown to have no perceptible effect on the speed and accuracy of the detection scheme,thus ensuring its reliability and stability.

关键词： Fault detection short-circuit fault multi-terminal direct current systems based on modular multilevel converter support vector machine(SVM) wavelet transform

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Dependence of Complex Magnetic Susceptibility on Alignment of Easy Axis in Magnetic Nanoparticles

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Journal of the Magnetics Society of Japan 2024年第6期48卷 116-123页

作者： Li, Menghao Trisnanto, Suko Bagus Ota, Satoshi Takemura, Yasushi Department of Electrical and Computer Engineering Yokohama National University Yokohama240-8501 Japan Department of Electrical and Electronic Engineering Shizuoka University Hamamatsu432-8561 Japan

Superparamagnetic nanoparticles have received significant attention with regard to medical applications of magnetic hyperthermia and magnetic nanoparticle imaging. For magnetic nanoparticles with uniaxial anisotropy, the coexistence of interwell and intrawell modes delays the magnetization response to the applied magnetic field. Therefore, an investigation of these two modes is essential for the study of magnetic moment dynamics. This study focuses on the frequency dependence of AC susceptibility to differentiate samples with varying degrees of easy axis alignment. The results indicate that the alignment of the easy axis separated the two modes of susceptibility. The variation in the activation energy depending on the degree of the easy axis alignment is also discussed, which clarifies the magnetization dynamics and Néel relaxation time of the magnetic nanoparticles. © 2024, Magnetics Society of Japan. All rights reserved.

关键词： Magnetic moments

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RFFI Protocols Using Antenna Mutual Coupling and Power Amplifier Nonlinear Memory Effects

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IEEE Communications Letters 2025年第6期29卷 1250-1254页

作者： Li, Yuepei Podilchak, Symon K. Zhang, Junqing Cotton, Simon L. Ratnarajah, Tharmalingam Ding, Yuan University of Edinburgh Institute of Digital Communications School of Engineering United Kingdom University of Liverpool Department of Electrical Engineering and Electronic United Kingdom Queen's University Department of Electrical Engineering and Computer Science Belfast United Kingdom San Diego State University College of Engineering Electrical and Computer Engineering San Diego United States United Kingdom

This paper presents a radio frequency fingerprinting identification (RFFI) protocol in wireless links with multi-antenna array transmitters. Multi-antenna systems are widely used in wireless communication systems for diversity and/or multiplexing. The mutual coupling (MC) effects arising from electromagnetic interactions between adjacent array elements can influence the RF characteristics of the transmitter and eventually the performance of the established links. In this paper, a novel RFF strategy is proposed to expand the differences in the RFF characteristics among wireless devices from the same vendor, with the goal of massively improving RFF classification accuracy in low to medium signal-to-noise ratio (SNR) channel conditions. Experimental results show that when classifying six power amplifiers (PAs) from the same vendor, 21% to 62% average classification accuracy improvement can be achieved by enlarging the RFF feature differences arising from the PA nonlinearity arising from the array coupling. © 1997-2012 IEEE.

关键词： Power amplifiers

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Nonlinear Dynamic Inversion-based Motion Planning of a Floating Satellite Platform

Nonlinear Dynamic Inversion-based Motion Planning of a Float...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Banerjee, Avijit Tevetzidis, Ilias Satpute, Sumeet Gajanan Nikolakopoulos, George Robotics and AI research group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This article presents a nonlinear dynamic inversion-based motion plan for a levitating robotic satellite emulation platform. The frictionless motion of such a levitating platform has dynamic equivalency with a satellite’s realistic movement in space, thus evolving as an efficient demonstration tool as a hardware-in-loop satellite motion simulator. A brief design description of the emulation platform unified with various sensor and actuator units is presented, and an associated nonlinear mathematical model representing its coupled dynamic motion is described. The proposed control design architecture manipulates the associated nonlinear dynamics, which appear due to the coupling of translational and rotational movement of the robotic platform, thereby establishing an efficient trajectory tracking capability for various operating regions without the additional requirement of gain scheduling. In order to realize the control requirement through a set of ON-OFF thruster-based actuation units, which closely resembles the reaction control system of realistic satellite design, an optimal thrust allocation logic is proposed that accounts for various physical limitations of thrusters such as thrusters as its magnitude constraint and minimum on time. The efficacy of the proposed modelling and control scheme is experimentally validated in different realistic motion planning scenarios, such as point-to-point manoeuvres with terminal objectives and a superior path-following capability. The experimental studies are supported with related results. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Motion planning

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Effects of Image Normalization on CNN-Based EEG-EMG Fusion

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IEEE Sensors Journal 2025年第11期25卷 20894-20906页

作者： Tryon, Jacob Guillermo Colli Alfaro, J. Trejos, Ana Luisa Western University Department of Electrical and Computer Engineering LondonONN6A 5B9 Canada Western University Department of Electrical and Computer Engineering School of Biomedical Engineering LondonONN6A 5B9 Canada

The rise in popularity of wearable robotic devices has brought many opportunities in the area of assistive devices for rehabilitation. However, despite their numerous advantages, these wearable mechatronic devices are not widely adopted due to a poor interaction between the device and the wearer. To solve this issue, several studies have proposed the use of sensor fusion of electroencephalography (EEG) and electromyography (EMG) signals using Convolutional Neural Networks (CNN) to detect the motion intention of the user and control the wearable device. Although normalization techniques can be applied during data pre-processing in order to improve performance, the correct normalization methods to apply for combined EEG and EMG data are unknown, hindering the potential improvement of the resulting CNN models. Therefore, in this study, no normalization, subject-wise, speed-wise, image-wise, and channel-wise normalization methods were compared. The effectiveness of these methods was tested on the overall and speed specific accuracies of CNN models trained using a database of combined EEG-EMG data collected during elbow flexion-extension motions at different speeds. The results of this study showed that no normalization improved the performance of the overall accuracy of CNN models, with grouped spectrogram-based models achieving an accuracy of 81.57 ± 7.11%. A similar trend was found for speed specific accuracies, in which no normalization showed to be a slightly better option during slow motions. Overall, these results provide information on the different tools that can be used to improve the performance of CNN-based models used for the control of wearable robotic devices. © 2001-2012 IEEE.

关键词： Electromyography

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