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LightSTATE: A Generalized Framework for Real-Time Human Activity Detection Using Edge-Based Video Processing and Vision Language Models

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IEEE Access 2025年 13卷 97609-97627页

作者： Debnath, Anik Kim, Yong-Woon Byun, Yung-Cheol Jeju National University Department of Computer Engineering Jeju-si63243 Korea Republic of Jeju National University Institute of Information Science & Technology Department of Computer Engineering Major of Electronic Engineering Jeju63243 Korea Republic of

Human activity detection plays a vital role in applications such as healthcare monitoring, smart environments, and security surveillance. However, traditional methods often rely on computationally intensive models, which are unsuitable for edge devices due to their limited resources and high latency. This research introduces a new approach named LightSTATE, a lightweight hybrid framework designed for real-time activity detection by integrating edge-based preprocessing with cloud-hosted Vision Language Models (VLMs). The system processes video streams through efficient frame extraction, edge detection and Root Mean Square Error (RMSE)-based frame filtering to identify significant motion events. These selected frames are transmitted to the cloud for semantic analysis and state recognition. The system utilizes GPT-4o as the vision-language model to generate rich, descriptive captions for human state understanding. LightSTATE was evaluated on a curated dataset of 9 real-world videos containing 634 frames, with 320 labeled frames used for testing. The framework demonstrated high accuracy in detecting predefined states, with an average precision of 0.98, an average recall of 0.98, and an average F1-score of 0.98. The experimental results confirm that the average frame processing time is approximately 0.8-0.9 seconds, ensuring suitability for real-time applications. Due to the scarcity of publicly accessible datasets, we compiled a custom dataset to effectively assess the performance of our proposed approach. The results validate the scalability and real-time capabilities of our proposed system, making it a promising solution for continuous monitoring applications. This study establishes LightSTATE as a scalable, efficient, and privacy-preserving framework for real-time human activity detection. Future work will focus on extending its applicability to dynamic and multi-person scenarios while enhancing system adaptability for diverse use cases. © 2013 IEEE.

关键词： Edge detection

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Trade Ease with Machine Learning and AWS

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IEEE Access 2023年 11卷 25893-25905页

作者： Teja, Kamurthi Ravi Liu, Chuan-Ming National Taipei University of Technology International Program of Electrical Engineering and Computer Science Taipei10608 Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei10608 Taiwan

Global trading is undergoing significant changes, necessitating modifications to the trading strategies. This study presents a newly developed cloud-based trading strategy that uses Amazon Web Services (AWS), machine learning (ML), and data science to automate trading tasks. The study begins by creating a machine learning trading strategy using a customized deep neural network (DNN). The strategy was then tested using a trading station before deployment on a cloud machine. The execution of the strategy resulted in a total profit of 42.74526 USD, with a test accuracy score of 87.45% and a training accuracy score of 89.15% over 6047 epochs. The roadmap provides a step-by-step overview of the entire process from strategy development to execution. In addition, this study offers insights into related issues and solutions that can enhance the effectiveness of trading strategies. Overall, this study contributes significantly to the field of cloud-based trading strategies and opens avenues for future research. © 2013 IEEE.

关键词： Deep neural networks

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Deep transfer learning technique to detect white blood cell classification in regular clinical practice using histopathological images

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Multimedia Tools and Applications 2025年第9期84卷 5699-5723页

作者： Davamani, K. Anita Jawahar, Malathy Anbarasi, L. Jani Ravi, Vinayakumar Al Mazroa, Alanoud Robin, C. R. Rene Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Leather Process Technology Division CSIR-Central Leather Research Institute Chennai India School of Computing Science and Engineering Vellore Institute of Technology Vellore India Computer Science and Engineering Sri Sairam Engineering College Sirukalathur India Center for Artificial Intelligence Prince Mohammad Bin Fahd University Khobar Saudi Arabia Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh11671 Saudi Arabia

Leukemia, a malignant disease characterized by the rapid proliferation of specific types of white blood cells (WBC), has prompted increased interest in leveraging automatic WBC classification system. This study presents the design of a robust WBC classification system, integrating deep learning with microscopic image analysis. The proposed classification model is designed to categorize blood cells into four distinct groups: eosinophil, lymphocyte, monocyte, and neutrophil. The study employs a Kaggle image dataset for comprehensive learning. The dataset comprises 12,500 microscopic images used to categorize the four blood cell groups. To enhance performance and reduce the likelihood of overfitting, transfer learning techniques are employed. Six deep transfer learning models namely VGG16, ResNet50, AlexNet, MobileNet, GoogLeNet, and EfficientNetBO are used for feature extraction and classification. The results of the experiments show that VGG16 and MobileNet demonstrated enhancements compared to other pre-trained models when evaluated on both augmented and original datasets. A diverse set of evaluation criteria was employed to thoroughly assess the effectiveness of medical image classification. Notably, the VGG16 and MobileNet models accurately predicted Lymphocytes and Monocytes with a 100% accuracy rate, and Eosinophil and Neutrophil with rates of 99.35% and 99.81%, respectively. This research work empower medical practitioners, particularly in the field of pathology and hematology by providing advanced tools for accurate blood cell classification. The proposed VGG16 and MobileNet models hold promise for simplifying WBC classification, improving decision-making processes, and ultimately advancing patient care in the medical domain. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Deep learning

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Prioritization and meta-heuristic approach for efficient congestion control in vehicular ad hoc networks (VANETs)

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International Journal of information technology (Singapore) 2025年 1-9页

作者： Sharma, Swati Khanum, Saba Madhumala, R.B. Maroju, Abhilash Aggarwal, Saurabh Department of Computer Science and Engineering Thapar Institute of Engineering and Technology Punjab India Department of Computer Science and Engineering MSIT Janakpuri Delhi India Department of Computer Science and Engineering Dayanand Sagar Academy of Technology and Management (DSATM) Bengaluru India Department of Computer Science and Engineering University of Cumberlands Williamsburg United States Department of Information Technology University of the Cumberlands Williamsburg United States

Vehicular ad hoc networks (VANETs) have emerged as a key area of interest in the research community due to their wide range of applications. As the number of vehicles increases, VANETs encounter challenges with access control, which affects communication between the source vehicle and other vehicles. To overcome this issue, the prioritization and meta-heuristic-based congestion control (PMCC) scheme is proposed in the given paper. It addresses this congestion by prioritizing messages and dynamically adjusting the transmission rate of safety messages. In the prioritization phase, message priority is determined using both dynamic and static factors. Then, to control channel load within VANETs, the PMCC scheme employs a Tabu Search optimization (TSO) algorithm to adjust the transmission rate of beacon messages. Comparative analysis of the PMCC scheme with existing schemes such as urban vehicular broadCAST (UV-CAST), distributed-fair power adjustment for the vehicular environment (D-FPAV), and loss differentiation rate adaptation (LORA) is conducted based on metrics including reception probability, average delay, and vehicle coverage ratio. The results show the superior performance of the proposed PMMC scheme in all aspects. © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： Decentralized congestion control (DCC) Distributed-fair power adjustment for the vehicular environment (D-FPAV) Loss differentiation rate adaptation (LORA) PMCC TSO Urban vehicular broadCAST (UV-CAST) VANETs

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Multimodal emotion recognition model via hybrid model with improved feature level fusion on facial and EEG feature set

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Multimedia Tools and Applications 2025年第1期84卷 1-36页

作者： Singh, Pratima Tripathi, Mukesh Kumar Patil, Mithun B. Shivendra Neelakantappa, Madugundu Department of Computer Science and Engineering Galgotias University Gautam Buddh Nagar Uttar Pradesh India Department of Computer Science and Engineering Vardhaman College of Engineering Telangana Hyderabad India Department of Computer Science and Engineering N K Orchid College of Engineering & Technology Maharastra Solapur India Department of Computer Application D. K. College Dumraon Bihar Buxar India Department of Information Technology Vasavi College of Engineering Telangana Hyderabad India

In recent years, academics have placed a high value on multi-modal emotion identification, as well as extensive research has been conducted in the areas of video, text, voice, and physical signal emotion detection. This paper proposes a novel multimodal emotion recognition model that employs a hybrid model with AMIG-based feature fusion on facial and EEG feature sets. The EEG signal and facial image are subjected to preprocessing to remove unwanted background noises with the Butterworth filter and Viola Jones Algorithm, respectively. While considering the pre-processed EEG signal, features such as EWFS-transform, wavelet features, and CSP-based features are extracted. In the proposed EWFS-transform, the window function is modified by using the frequency function and updated STFT. Conversely, the features including SE-AMM-EST-based features;LGXP and GLCM are extracted while considering the preprocessed face image. In the proposed SE-AMM-EST-based features, the mean of shape is updated and covariance in PCA for extracting texture-based features. In order to extract redundant free essential features, AMIG-based feature fusion is proposed. Further, the fused features are fed into a proposed hybrid model that includes LSTM and AML-CNN models. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Textures

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Neuroadaptive Containment Control for Nonlinear Multiagent Systems With Input Saturation: An Event-Triggered Communication Approach

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3163-3173页

作者： Wang, Xin Zhang, Sen Li, Huaqing Zhang, Wei Li, Hongyi Huang, Tingwen Southwest University College of Electronic and Information Engineering Chongqing400715 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

In this article, a neuroadaptive event-triggered containment control strategy combined with the dynamic surface control (DSC) approach is proposed for nonlinear multiagent systems (MASs) with input saturation. Based on the event-triggered communication mechanisms, the updates of neural network weight and controllers are implemented solely under triggering conditions of violation, which markedly reduces unnecessary communication resources and minimizes inefficient control costs compared with the traditional control method. Radial basis function neural networks (RBF NNs) are employed to handle the nonlinear uncertainties of MASs. Simultaneously, an adaptive compensatory mechanism is incorporated within the backstepping process to address the nonlinear effect posed by input saturation. Additionally, we demonstrate the system stability by extending the Lyapunov theorem to jump and continuous scenarios while excluding Zeno behavior, realizing that all followers can enter the convex hull constructed by leaders. Finally, the effectiveness of the proposed methodology is verified through application simulations. © 2013 IEEE.

关键词： Radial basis function networks

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Research on reflection properties of Ag-AAO-Al microstructures

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Optoelectronics and Advanced Materials, Rapid Communications 2023年第7-8期17卷 317-322页

作者： Cai, Yong Hou, Shuling Zhou, Huiying School of Computer and Information Engineering Central South University of Forestry Science and Technology Changsha410004 China

The reflection spectra of the microstructures with different AAO thickness, different AAO pore size and different kinds of liquids in AAO films were obtained experimentally and simulated based on COMSOL at the perpendicular incidence of 450-1150 nm. The results show that the variation of reflection spectra of the Ag-AAO-Al microstructure depends on the thickness, pore size of the AAO films, and effective refractive index of liquids. There is a good agreement between the experimental and simulated results, which can help to promote the application of metal-AAO-metal microstructure in reflection filters, images and liquid sensors etc. © 2023, National Institute of Optoelectronics. All rights reserved.

关键词： Microstructure

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Towards Blockchain-Based Secure BGP Routing,Challenges and Future Research Directions

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computers, Materials & Continua 2024年第5期79卷 2035-2062页

作者： Qiong Yang Li Ma Shanshan Tu Sami Ullah MuhammadWaqas Hisham Alasmary Faculty of Information Technology Beijing University of TechnologyBeijing100124China School of Information Science and Technology North China University of TechnologyBeijing100144China Department of Computer Science Shaheed Benazir Bhutto UniversitySheringal18050Pakistan School of Computing and Mathematical Science Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUK School of Engineering Edith Cowan UniversityPerth6027Australia Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Border Gateway Protocol(BGP)is a standard inter-domain routing protocol for the Internet that conveys network layer reachability information and establishes routes to different *** BGP protocol exhibits security design defects,such as an unconditional trust mechanism and the default acceptance of BGP route announcements from peers by BGP neighboring nodes,easily triggering prefix hijacking,path forgery,route leakage,and other BGP security ***,the traditional BGP security mechanism,relying on a public key infrastructure,faces issues like a single point of failure and a single point of *** decentralization,anti-tampering,and traceability advantages of blockchain offer new solution ideas for constructing secure and trusted inter-domain routing *** this paper,we summarize the characteristics of BGP protocol in detail,sort out the BGP security threats and their ***,we analyze the shortcomings of the traditional BGP security mechanism and comprehensively evaluate existing blockchain-based solutions to address the above problems and validate the reliability and effectiveness of blockchain-based BGP security methods in mitigating BGP security ***,we discuss the challenges posed by BGP security problems and outline prospects for future research.

关键词： BGP security blockchain prefix hijacking trust model secure routing

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Defect classification of glass substrate using deep neuro-fuzzy network with optimal parameter combination

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Granular Computing 2023年第4期8卷 839-849页

作者： Zhuang, Shun-Jie Lin, Cheng-Jian Department of Computer Science and Information Engineering National Chin-Yi University of Technology Taichung41107 Taiwan

Currently, numerous smart products are based on glass substrates. However, defects that occur during the production of glass substrates affect the quality and safety of the final products. Accordingly, we developed an optimal-parameter-combination-based deep neuro-fuzzy network (O-DNFN) for classifying defects in glass substrate images. The proposed O-DNFN comprises a deep neuro-fuzzy network (DNFN) and uses the Taguchi method. The fusion layer of the DNFN uses four feature fusion methods. The neuro-fuzzy network in the DNFN serves as replacement to a fully connected network for the classification of defects in glass substrate images. Because O-DNFN model parameter selection is challenging, we used the Taguchi method to determine the optimal parameter combination through fewer experiments. The experimental results revealed that the accuracy rates of the proposed O-DNFN with global max pooling fusion and an LeNet model in classifying defects in glass substrate images were 91.8% and 88%, respectively. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Defects

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A Review of Device-Free Indoor Positioning for Home-Based Care of the Aged:Techniques and Technologies

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computer Modeling in engineering & sciences 2023年第6期135卷 1901-1940页

作者： Geng Chen Lili Cheng Rui Shao Qingbin Wang Shuihua Wang College of Electronic and Information Engineering Shandong University of Science and TechnologyQingdao266590China School of Computer Science and Technology Henan Polytechnic UniversityJiaozuo454000China

With the development of urbanization,the problem of neurological diseases brought about by population aging has gradually become a social problem of worldwide *** leads to gradual degeneration of the central nervous system,shrinkage of brain tissue,and decline in physical function in many elderlies,making them susceptible to neurological diseases such as Alzheimer’s disease(AD),stroke,Parkinson’s and major depressive disorder(MDD).Due to the influence of these neurological diseases,the elderly have troubles such as memory loss,inability to move,falling,and getting lost,which seriously affect their quality of *** and positioning of elderly with neurological diseases and keeping track of their location in real-time are necessary and crucial in order to detect and treat dangerous and unexpected situations in *** that the elderly with neurological diseases forget to wear a positioning device or have mobility problems due to carrying a positioning device,device-free positioning as a passive positioning technology that detects device-free individuals is more suitable than traditional active positioning for the home-based care of the elderly with neurological *** paper provides an extensive and in-depth survey of device-free indoor positioning technology for home-based care and an in-depth analysis of the main features of current positioning systems,as well as the techniques,technologies andmethods they employ,fromthe perspective of the needs of the elderly with neurological ***,evaluation criteria and possible solutions of positioning techniques for the home-based care of the elderly with neurological conditions are ***,the opportunities and challenges for the development of indoor positioning technology in 6G mobile networks for home-based care of the elderly with neurological diseases are *** review has provided comprehensive and effective tracking and positioning techniques,technologies

关键词： Home-based care device-free neurological diseases indoor positioning positioning techniques and technologies positioning accuracy

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