Jing Zhang^1,2, Xin Qi^3,*, San Hlaing Myint³, Zheng Wen⁴

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2809-2809, 2021, DOI:10.32604/cmc.2021.17410

Abstract This article has no abstract. More >

Shabir Ahmad¹, Jehad Ali², Faisal Jamil³, Taeg Keun Whangbo¹, DoHyeun Kim^3,*

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1271-1288, 2021, DOI:10.32604/cmc.2021.017773

Abstract Smart cities have different contradicting goals having no apparent solution. The selection of the appropriate solution, which is considered the best compromise among the candidates, is known as complex problem-solving. Smart city administrators face different problems of complex nature, such as optimal energy trading in microgrids and optimal comfort index in smart homes, to mention a few. This paper proposes a novel architecture to offer complex problem solutions as a service (CPSaaS) based on predictive model optimization and optimal task orchestration to offer solutions to different problems in a smart city. Predictive model optimization uses a machine learning module and… More >

Mohana Priya Pitchai¹, Manikandan Ramachandran^1,*, Fadi Al-Turjman², Leonardo Mostarda³

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3947-3966, 2021, DOI:10.32604/cmc.2021.015568

Abstract The Internet of Things plays a predominant role in automating all real-time applications. One such application is the Internet of Vehicles which monitors the roadside traffic for automating traffic rules. As vehicles are connected to the internet through wireless communication technologies, the Internet of Vehicles network infrastructure is susceptible to flooding attacks. Reconfiguring the network infrastructure is difficult as network customization is not possible. As Software Defined Network provide a flexible programming environment for network customization, detecting flooding attacks on the Internet of Vehicles is integrated on top of it. The basic methodology used is crypto-fuzzy rules, in which cryptographic… More >

Jing Zhang^1,2, Xin Qi^3,*, San Hlaing Myint³, Zheng Wen⁴

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2807-2824, 2021, DOI:10.32604/cmc.2021.017410

Abstract With increasingly more smart cameras deployed in infrastructure and commercial buildings, 3D reconstruction can quickly obtain cities’ information and improve the efficiency of government services. Images collected in outdoor hazy environments are prone to color distortion and low contrast; thus, the desired visual effect cannot be achieved and the difficulty of target detection is increased. Artificial intelligence (AI) solutions provide great help for dehazy images, which can automatically identify patterns or monitor the environment. Therefore, we propose a 3D reconstruction method of dehazed images for smart cities based on deep learning. First, we propose a fine transmission image deep convolutional… More >

Najla Al-Nabhan^*, Maha AlDuhaim, Sarah AlHussan, Haifa Abdullah, Mnira AlHaid, Rawan AlDuhaishi

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1831-1845, 2021, DOI:10.32604/cmc.2021.012231

Abstract Simulation is a powerful tool for improving, evaluating and analyzing the performance of new and existing systems. Traffic simulators provide tools for studying transportation systems in smart cities as they describe the evolution of traffic to the highest level of detail. There are many types of traffic simulators that allow simulating traffic in modern cities. The most popular traffic simulation approach is the microscopic traffic simulation because of its ability to model traffic in a realistic manner. In many cities of Saudi Arabia, traffic management represents a major challenge as a result of expansion in traffic demands and increasing number… More >

Nabeela Awan¹, Salman Khan², Mohammad Khalid Imam Rahmani³, Muhammad Tahir³, Nur Alam MD^4,*, Ryan Alturki⁵, Ihsan Ullah⁶

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2449-2462, 2021, DOI:10.32604/cmc.2021.014386

Abstract Recent advancements in hardware and communication technologies have enabled worldwide interconnection using the internet of things (IoT). The IoT is the backbone of smart city applications such as smart grids and green energy management. In smart cities, the IoT devices are used for linking power, price, energy, and demand information for smart homes and home energy management (HEM) in the smart grids. In complex smart grid-connected systems, power scheduling and secure dispatch of information are the main research challenge. These challenges can be resolved through various machine learning techniques and data analytics. In this paper, we have proposed a particle… More >

Sulaiman Khan¹, Shah Nazir¹, Habib Ullah Khan^2,*

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 895-915, 2021, DOI:10.32604/cmc.2021.013878

Abstract During the last decade the emergence of Internet of Things (IoT) based applications inspired the world by providing state of the art solutions to many common problems. From traffic management systems to urban cities planning and development, IoT based home monitoring systems, and many other smart applications. Regardless of these facilities, most of these IoT based solutions are data driven and results in small accuracy values for smaller datasets. In order to address this problem, this paper presents deep learning based hybrid approach for the development of an IoT-based intelligent home security and appliance control system in the smart cities.… More >

Norah Saleh Alghamdi^1,*, Mohammad Ayoub Khan²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2509-2524, 2021, DOI:10.32604/cmc.2021.014180

Abstract Wireless sensor networks (WSNs) and Internet of Things (IoT) have gained more popularity in recent years as an underlying infrastructure for connected devices and sensors in smart cities. The data generated from these sensors are used by smart cities to strengthen their infrastructure, utilities, and public services. WSNs are suitable for long periods of data acquisition in smart cities. To make the networks of smart cities more reliable for sensitive information, the blockchain mechanism has been proposed. The key issues and challenges of WSNs in smart cities is efficiently scheduling the resources; leading to extending the network lifetime of sensors.… More >

Yongjun Ren^1,2, Kui Zhu^1,2, Yuqiu Gao³, Jinyue Xia^4,*, Shi Zhou^1,2, Ruiguo Hu^1,2, Xiujuan Feng⁵

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3271-3287, 2021, DOI:10.32604/cmc.2021.011153

Abstract Under the co-promotion of the wave of urbanization and the rise of data science, smart cities have become the new concept and new practice of urban development. Smart cities are the combination of information technology represented by the Internet of Things, cloud computing, mobile networks and big data, and urbanization. How to effectively achieve the long-term preservation of massive, heterogeneous, and multi-source digital electronic records in smart cities is a key issue that must be solved. Digital continuity can ensure the accessibility, integrity and availability of information. The quality management of electronic record, like the quality management of product, will… More >

Dildar Hussain¹, Muhammad Adnan Khan^2,*, Sagheer Abbas³, Rizwan Ali Naqvi⁴, Muhammad Faheem Mushtaq⁵, Abdur Rehman³, Afrozah Nadeem²

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 141-156, 2021, DOI:10.32604/cmc.2020.013458

Abstract The fast-paced growth of artificial intelligence provides unparalleled opportunities to improve the efficiency of various industries, including the transportation sector. The worldwide transport departments face many obstacles following the implementation and integration of different vehicle features. One of these tasks is to ensure that vehicles are autonomous, intelligent and able to grow their repository of information. Machine learning has recently been implemented in wireless networks, as a major artificial intelligence branch, to solve historically challenging problems through a data-driven approach. In this article, we discuss recent progress of applying machine learning into vehicle networks for intelligent route decision and try… More >