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  • Open Access

    ARTICLE

    A Multi-Mode Public Transportation System Using Vehicular to Network Architecture

    Settawit Poochaya1,*, Peerapong Uthansakul1, Monthippa Uthansakul1, Patikorn Anchuen2, Kontorn Thammakul3, Arfat Ahmad Khan4, Niwat Punanwarakorn5, Pech Sirivoratum5, Aranya Kaewkrad5, Panrawee Kanpan5, Apichart Wantamee5

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5845-5862, 2022, DOI:10.32604/cmc.2022.031162 - 28 July 2022

    Abstract The number of accidents in the campus of Suranaree University of Technology (SUT) has increased due to increasing number of personal vehicles. In this paper, we focus on the development of public transportation system using Intelligent Transportation System (ITS) along with the limitation of personal vehicles using sharing economy model. The SUT Smart Transit is utilized as a major public transportation system, while MoreSai@SUT (electric motorcycle services) is a minor public transportation system in this work. They are called Multi-Mode Transportation system as a combination. Moreover, a Vehicle to Network (V2N) is used for developing… More >

  • Open Access

    ARTICLE

    Sustainable Energy Management with Traffic Prediction Strategy for Autonomous Vehicle Systems

    Manar Ahmed Hamza1,*, Masoud Alajmi2, Jaber S. Alzahrani3, Siwar Ben Haj Hassine4, Abdelwahed Motwakel1, Ishfaq Yaseen1

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3465-3479, 2022, DOI:10.32604/cmc.2022.026066 - 29 March 2022

    Abstract Recent advancements of the intelligent transportation system (ITS) provide an effective way of improving the overall efficiency of the energy management strategy (EMSs) for autonomous vehicles (AVs). The use of AVs possesses many advantages such as congestion control, accident prevention, and etc. However, energy management and traffic flow prediction (TFP) still remains a challenging problem in AVs. The complexity and uncertainties of driving situations adequately affect the outcome of the designed EMSs. In this view, this paper presents novel sustainable energy management with traffic flow prediction strategy (SEM-TPS) for AVs. The SEM-TPS technique applies type More >

  • Open Access

    ARTICLE

    Hybrid Deep Learning Enabled Air Pollution Monitoring in ITS Environment

    Ashit Kumar Dutta1, Jenyfal Sampson2, Sultan Ahmad3, T. Avudaiappan4, Kanagaraj Narayanasamy5,*, Irina V. Pustokhina6, Denis A. Pustokhin7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1157-1172, 2022, DOI:10.32604/cmc.2022.024109 - 24 February 2022

    Abstract Intelligent Transportation Systems (ITS) have become a vital part in improving human lives and modern economy. It aims at enhancing road safety and environmental quality. There is a tremendous increase observed in the number of vehicles in recent years, owing to increasing population. Each vehicle has its own individual emission rate; however, the issue arises when the emission rate crosses a standard value. Owing to the technological advances made in Artificial Intelligence (AI) techniques, it is easy to leverage it to develop prediction approaches so as to monitor and control air pollution. The current research… More >

  • Open Access

    ARTICLE

    Intelligent DoS Attack Detection with Congestion Control Technique for VANETs

    R. Gopi1, Mahantesh Mathapati2, B. Prasad3, Sultan Ahmad4, Fahd N. Al-Wesabi5, Manal Abdullah Alohali6,*, Anwer Mustafa Hilal7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 141-156, 2022, DOI:10.32604/cmc.2022.023306 - 24 February 2022

    Abstract Vehicular Ad hoc Network (VANET) has become an integral part of Intelligent Transportation Systems (ITS) in today's life. VANET is a network that can be heavily scaled up with a number of vehicles and road side units that keep fluctuating in real world. VANET is susceptible to security issues, particularly DoS attacks, owing to maximum unpredictability in location. So, effective identification and the classification of attacks have become the major requirements for secure data transmission in VANET. At the same time, congestion control is also one of the key research problems in VANET which aims… More >

  • Open Access

    ARTICLE

    An Optimal Deep Learning for Cooperative Intelligent Transportation System

    K. Lakshmi1, Srinivas Nagineni2, E. Laxmi Lydia3, A. Francis Saviour Devaraj4, Sachi Nandan Mohanty5, Irina V. Pustokhina6,*, Denis A. Pustokhin7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 19-35, 2022, DOI:10.32604/cmc.2022.020244 - 24 February 2022

    Abstract Cooperative Intelligent Transport System (C-ITS) plays a vital role in the future road traffic management system. A vital element of C-ITS comprises vehicles, road side units, and traffic command centers, which produce a massive quantity of data comprising both mobility and service-related data. For the extraction of meaningful and related details out of the generated data, data science acts as an essential part of the upcoming C-ITS applications. At the same time, prediction of short-term traffic flow is highly essential to manage the traffic accurately. Due to the rapid increase in the amount of traffic… More >

  • Open Access

    ARTICLE

    Man Overboard Detection System Using IoT for Navigation Model

    Hüseyin Gürüler1, Murat Altun1, Faheem Khan2, Taegkeun Whangbo2,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4955-4969, 2022, DOI:10.32604/cmc.2022.023556 - 14 January 2022

    Abstract Security measures and contingency plans have been established in order to ensure human safety especially in the floating elements like ferry, ro-ro, catamaran, frigate, yacht that are the vehicles services for the purpose of logistic and passenger transport. In this paper, all processes in the event of Man overboard (MOB)are initiated for smart transportation. In MOB the falling person is totally dependent on the person who first saw the falling person. The main objective of this paper is to develop a solution to this significant problem. If a staff member or a passenger does not… More >

  • Open Access

    ARTICLE

    Gaining-Sharing Knowledge Based Algorithm for Solving Stochastic Programming Problems

    Prachi Agrawal1, Khalid Alnowibet2, Ali Wagdy Mohamed3,4,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2847-2868, 2022, DOI:10.32604/cmc.2022.023126 - 07 December 2021

    Abstract This paper presents a novel application of metaheuristic algorithms for solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithm is based on human behavior in which people gain and share their knowledge with others. Different types of stochastic fractional programming problems are considered in this study. The augmented Lagrangian method (ALM) is used to handle these constrained optimization problems by converting them into unconstrained optimization problems. Three examples from the literature are considered and transformed into their deterministic form using the chance-constrained technique. The transformed problems are More >

  • Open Access

    ARTICLE

    Modeling of Artificial Intelligence Based Traffic Flow Prediction with Weather Conditions

    Mesfer Al Duhayyim1, Amani Abdulrahman Albraikan2, Fahd N. Al-Wesabi3,4, Hiba M. Burbur5, Mohammad Alamgeer6, Anwer Mustafa Hilal7, Manar Ahmed Hamza7,*, Mohammed Rizwanullah7

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3953-3968, 2022, DOI:10.32604/cmc.2022.022692 - 07 December 2021

    Abstract Short-term traffic flow prediction (TFP) is an important area in intelligent transportation system (ITS), which is used to reduce traffic congestion. But the avail of traffic flow data with temporal features and periodic features are susceptible to weather conditions, making TFP a challenging issue. TFP process are significantly influenced by several factors like accident and weather. Particularly, the inclement weather conditions may have an extreme impact on travel time and traffic flow. Since most of the existing TFP techniques do not consider the impact of weather conditions on the TF, it is needed to develop… More >

  • Open Access

    ARTICLE

    Hypo-Driver: A Multiview Driver Fatigue and Distraction Level Detection System

    Qaisar Abbas1,*, Mostafa E.A. Ibrahim1,2, Shakir Khan1, Abdul Rauf Baig1

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1999-2007, 2022, DOI:10.32604/cmc.2022.022553 - 03 November 2021

    Abstract Traffic accidents are caused by driver fatigue or distraction in many cases. To prevent accidents, several low-cost hypovigilance (hypo-V) systems were developed in the past based on a multimodal-hybrid (physiological and behavioral) feature set. Similarly in this paper, real-time driver inattention and fatigue (Hypo-Driver) detection system is proposed through multi-view cameras and biosignal sensors to extract hybrid features. The considered features are derived from non-intrusive sensors that are related to the changes in driving behavior and visual facial expressions. To get enhanced visual facial features in uncontrolled environment, three cameras are deployed on multiview points… More >

  • Open Access

    ARTICLE

    Automatic License Plate Recognition System for Vehicles Using a CNN

    Parneet Kaur1, Yogesh Kumar1, Shakeel Ahmed2,*, Abdulaziz Alhumam2, Ruchi Singla3, Muhammad Fazal Ijaz4

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 35-50, 2022, DOI:10.32604/cmc.2022.017681 - 03 November 2021

    Abstract Automatic License Plate Recognition (ALPR) systems are important in Intelligent Transportation Services (ITS) as they help ensure effective law enforcement and security. These systems play a significant role in border surveillance, ensuring safeguards, and handling vehicle-related crime. The most effective approach for implementing ALPR systems utilizes deep learning via a convolutional neural network (CNN). A CNN works on an input image by assigning significance to various features of the image and differentiating them from each other. CNNs are popular for license plate character recognition. However, little has been reported on the results of these systems with More >

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