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  • Open Access

    REVIEW

    Computing Challenges of UAV Networks: A Comprehensive Survey

    Altaf Hussain1, Shuaiyong Li2, Tariq Hussain3, Xianxuan Lin4,*, Farman Ali5,*, Ahmad Ali AlZubi6

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 1999-2051, 2024, DOI:10.32604/cmc.2024.056183 - 18 November 2024

    Abstract Devices and networks constantly upgrade, leading to rapid technological evolution. Three-dimensional (3D) point cloud transmission plays a crucial role in aerial computing terminology, facilitating information exchange. Various network types, including sensor networks and 5G mobile networks, support this transmission. Notably, Flying Ad hoc Networks (FANETs) utilize Unmanned Aerial Vehicles (UAVs) as nodes, operating in a 3D environment with Six Degrees of Freedom (6DoF). This study comprehensively surveys UAV networks, focusing on models for Light Detection and Ranging (LiDAR) 3D point cloud compression/transmission. Key topics covered include autonomous navigation, challenges in video streaming infrastructure, motivations for More >

  • Open Access

    REVIEW

    Analyzing Real-Time Object Detection with YOLO Algorithm in Automotive Applications: A Review

    Carmen Gheorghe*, Mihai Duguleana, Razvan Gabriel Boboc, Cristian Cezar Postelnicu

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 1939-1981, 2024, DOI:10.32604/cmes.2024.054735 - 31 October 2024

    Abstract Identifying objects in real-time is a technology that is developing rapidly and has a huge potential for expansion in many technical fields. Currently, systems that use image processing to detect objects are based on the information from a single frame. A video camera positioned in the analyzed area captures the image, monitoring in detail the changes that occur between frames. The You Only Look Once (YOLO) algorithm is a model for detecting objects in images, that is currently known for the accuracy of the data obtained and the fast-working speed. This study proposes a comprehensive More >

  • Open Access

    ARTICLE

    A Novel Ego Lanes Detection Method for Autonomous Vehicles

    Bilal Bataineh*

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1941-1961, 2023, DOI:10.32604/iasc.2023.039868 - 21 June 2023

    Abstract Autonomous vehicles are currently regarded as an interesting topic in the AI field. For such vehicles, the lane where they are traveling should be detected. Most lane detection methods identify the whole road area with all the lanes built on it. In addition to having a low accuracy rate and slow processing time, these methods require costly hardware and training datasets, and they fail under critical conditions. In this study, a novel detection algorithm for a lane where a car is currently traveling is proposed by combining simple traditional image processing with lightweight machine learning… More >

  • Open Access

    ARTICLE

    A Trailblazing Framework of Security Assessment for Traffic Data Management

    Abdulaziz Attaallah1, Khalil al-Sulbi2, Areej Alasiry3, Mehrez Marzougui3, Neha Yadav4, Syed Anas Ansar5,*, Pawan Kumar Chaurasia4, Alka Agrawal4

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1853-1875, 2023, DOI:10.32604/iasc.2023.039761 - 21 June 2023

    Abstract Connected and autonomous vehicles are seeing their dawn at this moment. They provide numerous benefits to vehicle owners, manufacturers, vehicle service providers, insurance companies, etc. These vehicles generate a large amount of data, which makes privacy and security a major challenge to their success. The complicated machine-led mechanics of connected and autonomous vehicles increase the risks of privacy invasion and cyber security violations for their users by making them more susceptible to data exploitation and vulnerable to cyber-attacks than any of their predecessors. This could have a negative impact on how well-liked CAVs are with… More >

  • Open Access

    ARTICLE

    Sensor Data Based Anomaly Detection in Autonomous Vehicles using Modified Convolutional Neural Network

    Sivaramakrishnan Rajendar, Vishnu Kumar Kaliappan*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 859-875, 2022, DOI:10.32604/iasc.2022.020936 - 17 November 2021

    Abstract Automated Vehicles (AVs) reform the automotive industry by enabling real-time and efficient data exchange between the vehicles. While connectivity and automation of the vehicles deliver a slew of benefits, they may also introduce new safety, security, and privacy risks. Further, AVs rely entirely on the sensor data and the data from other vehicles too. On the other hand, the sensor data is susceptible to anomalies caused by cyber-attacks, errors, and faults, resulting in accidents and fatalities. Hence, it is essential to create techniques for detecting anomalies and identifying their sources before the wide adoption of More >

  • Open Access

    ARTICLE

    An Optimal Distribution of RSU for Improving Self-Driving Vehicle Connectivity

    Khattab Alheeti1, Abdulkareem Alaloosy1, Haitham Khalaf2, Abdulkareem Alzahrani3,*, Duaa Al_Dosary4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3311-3319, 2022, DOI:10.32604/cmc.2022.019773 - 27 September 2021

    Abstract Self-driving and semi-self-driving cars play an important role in our daily lives. The effectiveness of these cars is based heavily on the use of their surrounding areas to collect sensitive and vital information. However, external infrastructures also play significant roles in the transmission and reception of control data, cooperative awareness messages, and caution notifications. In this case, roadside units are considered one of the most important communication peripherals. Random distribution of these infrastructures will overburden the spread of self-driving vehicles in terms of cost, bandwidth, connectivity, and radio coverage area. In this paper, a new More >

  • Open Access

    ARTICLE

    Thermodynamics Inspired Co-operative Self-Organization of Multiple Autonomous Vehicles

    Ayesha Maqbool1,*, Farkhanda Afzal2, Tauseef Rana3, Alina Mirza4

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 653-667, 2021, DOI:10.32604/iasc.2021.017506 - 20 April 2021

    Abstract This paper presents a co-operative, self-organisation method for Multiple Autonomous Vehicles aiming to share surveillance responsibilities. Spatial organization or formation configuration of multiple vehicles/agents’ systems is crucial for a team of agents to achieve their mission objectives. In this paper we present simple yet efficient thermodynamic inspired formation control framework. The proposed method autonomously allocates region of surveillance to each vehicle and also re-adjusts the area of their responsibilities during the mission. It provides framework for heterogeneous UAVs to scatter themselves optimally in order to provide maximum coverage of a given area. The method is… More >

  • Open Access

    ARTICLE

    An Authentication Mechanism for Autonomous Vehicle ECU Utilizing a Novel Slice-Based PUF Design

    Jihai Yang1, Zongtao Duan1, Muyao Wang2, Jabar Mahmood1, Yuanyuan Xiao1, Yun Yang1,*

    Journal of New Media, Vol.2, No.4, pp. 157-165, 2020, DOI:10.32604/jnm.2020.014309 - 23 December 2020

    Abstract Modern autonomous vehicles are getting progressively popular and increasingly getting closer to the core of future development in transportation field. However, there is no reliable authentication mechanism for the unmanned vehicle communication system, this phenomenon draws attention about the security of autonomous vehicles of people in all aspects. Physical Unclonable Function (PUF) circuits is light-weight, and it can product unique and unpredictable digital signature utilizing the manufacturing variations occur in each die and these exact silicon features cannot be recreated theoretically. Considering security issues of communication between Electronic Control Units (ECUs) in vehicles, we propose… More >

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