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  • Open Access

    ARTICLE

    Performance Evaluation of Three-Dimensional UWB Real-Time Locating Auto-Positioning System for Fire Rescue

    Hang Yang1,2,3,*, Xunbo Li1, Witold Pedrycz2

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3039-3058, 2023, DOI:10.32604/iasc.2023.040412

    Abstract Fire rescue challenges and solutions have evolved from straightforward plane rescue to encompass 3D space due to the rise of high-rise city buildings. Hence, this study facilitates a system with quick and simplified on-site launching and generates real-time location data, enabling fire rescuers to arrive at the intended spot faster and correctly for effective and precise rescue. Auto-positioning with step-by-step instructions is proposed when launching the locating system, while no extra measuring instrument like Total Station (TS) is needed. Real-time location tracking is provided via a 3D space real-time locating system (RTLS) constructed using Ultra-wide Bandwidth technology (UWB), which requires… More >

  • Open Access

    ARTICLE

    An IoT-Based Aquaculture Monitoring System Using Firebase

    Wen-Tsai Sung1, Indra Griha Tofik Isa1,2, Sung-Jung Hsiao3,*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2179-2200, 2023, DOI:10.32604/cmc.2023.041022

    Abstract Indonesia is a producer in the fisheries sector, with production reaching 14.8 million tons in 2022. The production potential of the fisheries sector can be optimally optimized through aquaculture management. One of the most important issues in aquaculture management is how to efficiently control the fish pond water conditions. IoT technology can be applied to support a fish pond aquaculture monitoring system, especially for catfish species (Siluriformes), in real-time and remotely. One of the technologies that can provide this convenience is the IoT. The problem of this study is how to integrate IoT devices with Firebase’s cloud data system to… More >

  • Open Access

    PROCEEDINGS

    A Data-Driven Model for Real-Time Simulation of the Contact Detumbling of Satellites

    Hao Chen1, Honghua Dai1, Xiaokui Yue1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09145

    Abstract The number of malfunctioning satellites is dramatically increasing with the development of space technology in recent decades. These malfunctioning satellites are normally in rotating or tumbling states due to residual angular momentum, gravity gradient, et al, making direct capture impossible. Therefore, stabilizing these objects within acceptable angular velocities is an indispensable stage for in-orbit capture. The contact method using a flexible device (e.g., brush or rod) to detumble these satellites is considered to be safe and efficient enough. However, it is extremely time-consuming to solve the dynamic model of the detumbling system, which is a very tricky problem for in-orbit… More >

  • Open Access

    ARTICLE

    SlowFast Based Real-Time Human Motion Recognition with Action Localization

    Gyu-Il Kim1, Hyun Yoo2, Kyungyong Chung3,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2135-2152, 2023, DOI:10.32604/csse.2023.041030

    Abstract Artificial intelligence is increasingly being applied in the field of video analysis, particularly in the area of public safety where video surveillance equipment such as closed-circuit television (CCTV) is used and automated analysis of video information is required. However, various issues such as data size limitations and low processing speeds make real-time extraction of video data challenging. Video analysis technology applies object classification, detection, and relationship analysis to continuous 2D frame data, and the various meanings within the video are thus analyzed based on the extracted basic data. Motion recognition is key in this analysis. Motion recognition is a challenging… More >

  • Open Access

    ARTICLE

    Quick and Accurate Counting of Rapeseed Seedling with Improved YOLOv5s and Deep-Sort Method

    Chen Su, Jie Hong, Jiang Wang, Yang Yang*

    Phyton-International Journal of Experimental Botany, Vol.92, No.9, pp. 2611-2632, 2023, DOI:10.32604/phyton.2023.029457

    Abstract The statistics of the number of rapeseed seedlings are very important for breeders and planters to conduct seed quality testing, field crop management and yield estimation. Calculating the number of seedlings is inefficient and cumbersome in the traditional method. In this study, a method was proposed for efficient detection and calculation of rapeseed seedling number based on improved you only look once version 5 (YOLOv5) to identify objects and deep-sort to perform object tracking for rapeseed seedling video. Coordinated attention (CA) mechanism was added to the trunk of the improved YOLOv5s, which made the model more effective in identifying shaded,… More >

  • Open Access

    ARTICLE

    An Artificial Intelligence Algorithm for the Real-Time Early Detection of Sticking Phenomena in Horizontal Shale Gas Wells

    Qing Wang*, Haige Wang, Hongchun Huang, Lubin Zhuo, Guodong Ji

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.10, pp. 2569-2578, 2023, DOI:10.32604/fdmp.2023.025349

    Abstract Sticking is the most serious cause of failure in complex drilling operations. In the present work a novel “early warning” method based on an artificial intelligence algorithm is proposed to overcome some of the known problems associated with existing sticking-identification technologies. The method is tested against a practical case study (Southern Sichuan shale gas drilling operations). It is shown that the twelve sets of sticking fault diagnostic results obtained from a simulation are all consistent with the actual downhole state; furthermore, the results from four groups of verification samples are also consistent with the actual downhole state. This shows that… More >

  • Open Access

    ARTICLE

    Real-Time Multi Fractal Trust Evaluation Model for Efficient Intrusion Detection in Cloud

    S. Priya1, R. S. Ponmagal2,*

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1895-1907, 2023, DOI:10.32604/iasc.2023.039814

    Abstract Handling service access in a cloud environment has been identified as a critical challenge in the modern internet world due to the increased rate of intrusion attacks. To address such threats towards cloud services, numerous techniques exist that mitigate the service threats according to different metrics. The rule-based approaches are unsuitable for new threats, whereas trust-based systems estimate trust value based on behavior, flow, and other features. However, the methods suffer from mitigating intrusion attacks at a higher rate. This article presents a novel Multi Fractal Trust Evaluation Model (MFTEM) to overcome these deficiencies. The method involves analyzing service growth,… More >

  • Open Access

    ARTICLE

    Real-Time CNN-Based Driver Distraction & Drowsiness Detection System

    Abdulwahab Ali Almazroi1,*, Mohammed A. Alqarni2, Nida Aslam3, Rizwan Ali Shah4

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2153-2174, 2023, DOI:10.32604/iasc.2023.039732

    Abstract Nowadays days, the chief grounds of automobile accidents are driver fatigue and distractions. With the development of computer vision technology, a cutting-edge system has the potential to spot driver distractions or sleepiness and alert them, reducing accidents. This paper presents a novel approach to detecting driver tiredness based on eye and mouth movements and object identification that causes a distraction while operating a motor vehicle. Employing the facial landmarks that the camera picks up and sends to classify using a Convolutional Neural Network (CNN) any changes by focusing on the eyes and mouth zone, precision is achieved. One of the… More >

  • Open Access

    ARTICLE

    A Real-Time Pedestrian Social Distancing Risk Alert System for COVID-19

    Zhihan Liu1, Xiang Li1, Siqi Liu2, Wei Li1,*, Xiangxu Meng1, Jing Jia3

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 937-954, 2023, DOI:10.32604/csse.2023.039417

    Abstract The COVID-19 virus is usually spread by small droplets when talking, coughing and sneezing, so maintaining physical distance between people is necessary to slow the spread of the virus. The World Health Organization (WHO) recommends maintaining a social distance of at least six feet. In this paper, we developed a real-time pedestrian social distance risk alert system for COVID-19, which monitors the distance between people in real-time via video streaming and provides risk alerts to the person in charge, thus avoiding the problem of too close social distance between pedestrians in public places. We design a lightweight convolutional neural network… More >

  • Open Access

    ARTICLE

    Cyclists’ exposure to air pollution and noise in Mexico City

    Contribution of real-time traffic density indicators integrated into GIS

    Philippe Apparicio1 , Jérémy Gelb1, Paula Negron-Poblete2, Mathieu Carrier1, Stéphanie Potvin1 , Élaine Lesage-Mann1

    Revue Internationale de Géomatique, Vol.30, No.2, pp. 155-179, 2020, DOI:10.3166/rig.2021.00110

    Abstract Air pollution and road traffic noise are two important environmental nuisances that could be harmful to the health and well-being of urban populations. In Mexico City, as in many North American cities, there has been an upsurge in bicycle ridership. However, Mexico City is also well known for having high levels of noise and air pollution. The purpose of this study is threefold: 1) evaluate cyclists’ exposure to air pollution (nitrogen dioxide) and road traffic noise; 2) identify local factors that increase or reduce cyclists’ exposure, in paying particular attention to the type of road and bicycle path or lane… More >

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