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  • Open Access


    Real-Time Prediction of Urban Traffic Problems Based on Artificial Intelligence-Enhanced Mobile Ad Hoc Networks (MANETS)

    Ahmed Alhussen1, Arshiya S. Ansari2,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1903-1923, 2024, DOI:10.32604/cmc.2024.049260

    Abstract Traffic in today’s cities is a serious problem that increases travel times, negatively affects the environment, and drains financial resources. This study presents an Artificial Intelligence (AI) augmented Mobile Ad Hoc Networks (MANETs) based real-time prediction paradigm for urban traffic challenges. MANETs are wireless networks that are based on mobile devices and may self-organize. The distributed nature of MANETs and the power of AI approaches are leveraged in this framework to provide reliable and timely traffic congestion forecasts. This study suggests a unique Chaotic Spatial Fuzzy Polynomial Neural Network (CSFPNN) technique to assess real-time data… More >

  • Open Access


    Hybrid Algorithm-Driven Smart Logistics Optimization in IoT-Based Cyber-Physical Systems

    Abdulwahab Ali Almazroi1,*, Nasir Ayub2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3921-3942, 2023, DOI:10.32604/cmc.2023.046602

    Abstract Effectively managing complex logistics data is essential for development sustainability and growth, especially in optimizing distribution routes. This article addresses the limitations of current logistics path optimization methods, such as inefficiencies and high operational costs. To overcome these drawbacks, we introduce the Hybrid Firefly-Spotted Hyena Optimization (HFSHO) algorithm, a novel approach that combines the rapid exploration and global search abilities of the Firefly Algorithm (FO) with the localized search and region-exploitation skills of the Spotted Hyena Optimization Algorithm (SHO). HFSHO aims to improve logistics path optimization and reduce operational costs. The algorithm’s effectiveness is systematically… More >

  • Open Access


    An Intelligent Adaptive Dynamic Algorithm for a Smart Traffic System

    Ahmed Alsheikhy1,*, Yahia Said1, Tawfeeq Shawly2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1109-1126, 2023, DOI:10.32604/csse.2023.035135

    Abstract Due to excessive car usage, pollution and traffic have increased. In urban cities in Saudi Arabia, such as Riyadh and Jeddah, drivers and air quality suffer from traffic congestion. Although the government has implemented numerous solutions to resolve this issue or reduce its effect on the environment and residents, it still exists and is getting worse. This paper proposes an intelligent, adaptive, practical, and feasible deep learning method for intelligent traffic control. It uses an Internet of Things (IoT) sensor, a camera, and a Convolutional Neural Network (CNN) tool to control traffic in real time.… More >

  • Open Access


    A Neuro-Fuzzy Approach to Road Traffic Congestion Prediction

    Mohammed Gollapalli1, Atta-ur-Rahman2,*, Dhiaa Musleh2, Nehad Ibrahim2, Muhammad Adnan Khan3, Sagheer Abbas4, Ayesha Atta5, Muhammad Aftab Khan6, Mehwash Farooqui6, Tahir Iqbal7, Mohammed Salih Ahmed6, Mohammed Imran B. Ahmed6, Dakheel Almoqbil8, Majd Nabeel2, Abdullah Omer2

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 295-310, 2022, DOI:10.32604/cmc.2022.027925

    Abstract The fast-paced growth of artificial intelligence applications provides unparalleled opportunities to improve the efficiency of various systems. Such as the transportation sector faces many obstacles following the implementation and integration of different vehicular and environmental aspects worldwide. Traffic congestion is among the major issues in this regard which demands serious attention due to the rapid growth in the number of vehicles on the road. To address this overwhelming problem, in this article, a cloud-based intelligent road traffic congestion prediction model is proposed that is empowered with a hybrid Neuro-Fuzzy approach. The aim of the study… More >

  • Open Access


    A Novel Green IoT-Based Pay-As-You-Go Smart Parking System

    Andrea Sant1, Lalit Garg1,*, Peter Xuereb1, Chinmay Chakraborty2

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3523-3544, 2021, DOI:10.32604/cmc.2021.015265

    Abstract The better management of resources and the potential improvement in traffic congestion via reducing the orbiting time for parking spaces is crucial in a smart city, particularly those with an uneven correlation between the increase in vehicles and infrastructure. This paper proposes and analyses a novel green IoT-based Pay-As-You-Go (PAYG) smart parking system by utilizing unused garage parking spaces. The article also presents an intelligent system that offers the most favorable prices to its users by matching private garages’ pricing portfolio with a garage’s current demand. Malta, the world’s fourth-most densely populated country, is considered More >

  • Open Access


    Numerical Simulation and Natural Computing applied to a Real World Traffic Optimization Case under Stress Conditions:

    M.J. Galán Moreno, J.J. Sánchez Medina, L. Álvarez Álvarez E. Rubio Royo1

    CMES-Computer Modeling in Engineering & Sciences, Vol.50, No.3, pp. 191-226, 2009, DOI:10.3970/cmes.2009.050.191

    Abstract Urban traffic is a key factor for the development of a city. There exist many different approaches facing traffic optimization. In our case we have focused on traffic lights optimization. We have designed and tested a new architecture to optimize traffic light cycle times. The purpose of this research is to demonstrate the good performance of our architecture in a congested scenario. We have simulated several congestion situations for a very large real world traffic network - "La Almozara" in Zaragoza, Spain. Our results seem encouraging in this extreme situation. As we increase the load More >

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