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  • Open Access

    ARTICLE

    Resource Load Prediction of Internet of Vehicles Mobile Cloud Computing

    Wenbin Bi1, Fang Yu2, Ning Cao3,*, Russell Higgs4

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 165-180, 2022, DOI:10.32604/cmc.2022.027776 - 18 May 2022

    Abstract Load-time series data in mobile cloud computing of Internet of Vehicles (IoV) usually have linear and nonlinear composite characteristics. In order to accurately describe the dynamic change trend of such loads, this study designs a load prediction method by using the resource scheduling model for mobile cloud computing of IoV. Firstly, a chaotic analysis algorithm is implemented to process the load-time series, while some learning samples of load prediction are constructed. Secondly, a support vector machine (SVM) is used to establish a load prediction model, and an improved artificial bee colony (IABC) function is designed… More >

  • Open Access

    ARTICLE

    Autonomous Unmanned Aerial Vehicles Based Decision Support System for Weed Management

    Ashit Kumar Dutta1,*, Yasser Albagory2, Abdul Rahaman Wahab Sait3, Ismail Mohamed Keshta1

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 899-915, 2022, DOI:10.32604/cmc.2022.026783 - 18 May 2022

    Abstract Recently, autonomous systems become a hot research topic among industrialists and academicians due to their applicability in different domains such as healthcare, agriculture, industrial automation, etc. Among the interesting applications of autonomous systems, their applicability in agricultural sector becomes significant. Autonomous unmanned aerial vehicles (UAVs) can be used for suitable site-specific weed management (SSWM) to improve crop productivity. In spite of substantial advancements in UAV based data collection systems, automated weed detection still remains a tedious task owing to the high resemblance of weeds to the crops. The recently developed deep learning (DL) models have… More >

  • Open Access

    ARTICLE

    Recurrent Autoencoder Ensembles for Brake Operating Unit Anomaly Detection on Metro Vehicles

    Jaeyong Kang1, Chul-Su Kim2, Jeong Won Kang3, Jeonghwan Gwak1,4,5,6,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1-14, 2022, DOI:10.32604/cmc.2022.023641 - 18 May 2022

    Abstract The anomaly detection of the brake operating unit (BOU) in the brake systems on metro vehicle is critical for the safety and reliability of the trains. On the other hand, current periodic inspection and maintenance are unable to detect anomalies in an early stage. Also, building an accurate and stable system for detecting anomalies is extremely difficult. Therefore, we present an efficient model that use an ensemble of recurrent autoencoders to accurately detect the BOU abnormalities of metro trains. This is the first proposal to employ an ensemble deep learning technique to detect BOU abnormalities… More >

  • Open Access

    ARTICLE

    Modeling and Experimental Verification of Electric Vehicles Off-Grid Photovoltaic Powered Charging Station

    Essam Hendawi1,*, Sattam Al Otaibi1, Sherif Zaid2,3,4, Ayman Hoballah1, Salah K. ElSayed1, Nagy I. Elkalashy1, Yasser Ahmed1

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1009-1025, 2022, DOI:10.32604/csse.2022.022927 - 09 May 2022

    Abstract With the increasing development of EVs, the energy demand from the conventional utility grid increases in proportion. On the other hand, photovoltaic (PV) energy sources can overcome several problems when charging EVs from the utility grid especially in remote areas. This paper presents an effective photovoltaic stand-alone charging station for EV applications. The proposed charging station incorporates PV array, a lithium-ion battery representing the EV battery, and a lead-acid battery representing the energy storage system (ESS). A bidirectional DC-DC converter is employed for charging/discharging the ESS and a unidirectional DC-DC converter is utilized for charging… More >

  • Open Access

    ARTICLE

    Object Detection Learning for Intelligent Self Automated Vehicles

    Ahtsham Alam1, Syed Ahmed Abdullah1, Israr Akhter1, Suliman A. Alsuhibany2,*, Yazeed Yasin Ghadi3, Tamara al Shloul4, Ahmad Jalal1

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 941-955, 2022, DOI:10.32604/iasc.2022.024840 - 03 May 2022

    Abstract Robotics is a part of today's communication that makes human life simpler in the day-to-day aspect. Therefore, we are supporting this cause by making a smart city project that is based on Artificial Intelligence, image processing, and some touch of hardware such as robotics. In particular, we advocate a self automation device (i.e., autonomous car) that performs actions and takes choices on its very own intelligence with the assist of sensors. Sensors are key additives for developing and upgrading all forms of self-sustaining cars considering they could offer the information required to understand the encircling… More >

  • Open Access

    ARTICLE

    Data Offloading in the Internet of Vehicles Using a Hybrid Optimization Technique

    A. Backia Abinaya1,*, G. Karthikeyan2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 325-338, 2022, DOI:10.32604/iasc.2022.020896 - 15 April 2022

    Abstract The Internet of Vehicles (IoV) is utilized for collecting enormous real time information driven traffics and alert drivers depending on situations. In recent times, all smart vehicles are developed with IoT devices. These devices communicate with a radio access unit (RAU) at road side. Moreover, a 5G system is equipped with a base station and connection interfaces that use optic fiber for their effective communication. For a fast mode of communication, the IoV must offload its data to the nearest edge nodes. The main problem with the IoV is that it generates enormous data which… More >

  • Open Access

    ARTICLE

    A Novel Method for the Application of the ECMS (Equivalent Consumption Minimization Strategy) to Reduce Hydrogen Consumption in Fuel Cell Hybrid Electric Vehicles

    Wen Sun, Hao Liu, Ming Han, Ke Sun, Shuzhan Bai*, Guoxiang Li*

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.4, pp. 867-882, 2022, DOI:10.32604/fdmp.2022.018923 - 06 April 2022

    Abstract Fuel cell hybrid electric vehicles are currently being considered as ideal means to solve the energy crisis and global warming in today’s society. In this context, this paper proposes a method to solve the problem related to the dependence of the so-called optimal equivalent factor (determined in the framework of the equivalent consumption minimum strategy-ECMS) on the working conditions. The simulation results show that under typical conditions (some representative cities being considered), the proposed strategy can maintain the power balance; for different initial battery’s states of charge (SOC), after the SOC stabilizes, the fuel consumption More >

  • Open Access

    ARTICLE

    Intelligent Deep Data Analytics Based Remote Sensing Scene Classification Model

    Ahmed Althobaiti1, Abdullah Alhumaidi Alotaibi2, Sayed Abdel-Khalek3, Suliman A. Alsuhibany4, Romany F. Mansour5,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1921-1938, 2022, DOI:10.32604/cmc.2022.025550 - 24 February 2022

    Abstract Latest advancements in the integration of camera sensors paves a way for new Unmanned Aerial Vehicles (UAVs) applications such as analyzing geographical (spatial) variations of earth science in mitigating harmful environmental impacts and climate change. UAVs have achieved significant attention as a remote sensing environment, which captures high-resolution images from different scenes such as land, forest fire, flooding threats, road collision, landslides, and so on to enhance data analysis and decision making. Dynamic scene classification has attracted much attention in the examination of earth data captured by UAVs. This paper proposes a new multi-modal fusion… More >

  • Open Access

    ARTICLE

    Research on Ratio of New Energy Vehicles to Charging Piles in China

    Zhiqiu Yu*, Shuo-Yan Chou

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 963-984, 2022, DOI:10.32604/csse.2022.023129 - 08 February 2022

    Abstract With the widespread of new energy vehicles, charging piles have also been continuously installed and constructed. In order to make the number of piles meet the needs of the development of new energy vehicles, this study aims to apply the method of system dynamics and combined with the grey prediction theory to determine the parameters as well as to simulate and analyze the ratio of vehicles to chargers. Through scenario analysis, it is predicted that by 2030, this ratio will gradually decrease from 1.79 to 1. In order to achieve this ratio as 1:1, it More >

  • Open Access

    ARTICLE

    Towards Realistic Vibration Testing of Large Floor Batteries for Battery Electric Vehicles (BEV)

    Benedikt Plaumann*

    Sound & Vibration, Vol.56, No.1, pp. 1-19, 2022, DOI:10.32604/sv.2022.018634 - 10 January 2022

    Abstract This contribution shows an analysis of vibration measurement on large floor-mounted traction batteries of Battery Electric Vehicles (BEV). The focus lies on the requirements for a realistic replication of the mechanical environments in a testing laboratory. Especially the analysis on global bending transfer functions and local corner bending coherence indicate that neither a fully stiff fixation of the battery nor a completely independent movement on the four corners yields a realistic and conservative test scenario. The contribution will further show what implication these findings have on future vibration & shock testing equipment for large traction More >

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