Special lssues
Table of Content

The Next Generation of Artificial Intelligence and the Intelligent Internet of Things

Submission Deadline: 30 April 2023 (closed)

Guest Editors

Dr. Muhammad Hamid, University of Veterinary and Animal Sciences, Pakistan.
Dr. Adnan Ahmad, COMSATS University Islamabad, Pakistan.
Dr. Farrukh Zeshan, COMSATS University Islamabad, Pakistan.
Dr. Arshad Ahmad, Johannes Kepler University, Austria.
Dr. Riaz Ul Amin, University of Okara, Pakistan.
Dr. M. Usman Ashraf, GC Women University Sialkot, Pakistan.
Dr. Kiran Adnan, Universiti Tunku Abdul Rahman, Malaysia.

Summary

Artificial intelligence (AI) and Internet of Things (IoT) makes everyone's life easier. It mostly benefits the visually handicapped, the deaf & dumb, and old age people. It's been widely used with the IoT, making all of the job easier and allowing for the creation of smart surroundings. The IoT benefited greatly from the capacity to learn convolutional approaches of Artificial Intelligence. A new generation of IoT devices will bridge the gap between the physical and digital worlds, enhancing the quality and productivity of human life, society, and industry.
All industries, from smart homes to rocket launches, are being impacted by the potential of AI and IoT. The ability to develop intelligent systems capable of interacting with devices among themselves without the need for human intervention is the primary focus of research in this field. According to a recent survey, “IoT smart objects are expected to reach 314 billion entities deployed globally by the end of 2022,” according to the results. As an example, despite the fact that the number of connected devices already exceeds the number of humans on the planet by over 2 times, connecting systems and devices remains the top priority for the vast majority of businesses.
AI and the IoT are spearheading transformative mega-trends. The technologies, frameworks, and management paradigms associated with AI-based IoT, as well as their associated management paradigm, are already having a significant impact on many industries. The Internet of Things is further distinguished as an intelligent system by the use of Artificial Intelligence in a variety of applications such as Industrial Internet, Logistics and Supply Chain Management Systems, Health Care, Education (including online learning), Automotive Digital Technology, and Inventory Management.
• In this special issue, we will aim to provide a comprehensive exploration of the past and current frameworks for the Internet of Things, as well as how they are combined with Artificial Intelligence technologies. 
• Its goal is to compile the most recent research findings in emerging artificial intelligence methods for processing and storing data generated by the Internet of Things in one place.
• It covers the applications, techniques, algorithms, platforms, and tools used in IoT and AI systems in depth.
• Enhancement of an application and service marketplace in order to foster an IoT ecosystem.


Keywords

Suggested topics include, but are not limited to the following:
• Future challenges and applications of Intelligent IOT based AI
• Artificial intelligence in expert systems
• Revolution of Industry 4.0 to Industry 5.0
• Internet of Nano Things (IoNT)
• Industrial Internet of Things (IIoT)
• Internet of Medical Things (IoMT)
• Soft computing techniques in IoT based AI systems
• Next-generation enterprise systems
• Interoperability Development Testing of IoT
• Security and privacy issues in IoT AI systems
• Autonomous systems
• Deep learning-based intelligent systems
• Expert systems
• Fuzzy systems
• Intelligent/smart IoT
• Machine learning-based intelligent systems
• Smart Agriculture using IoT
• IoT in Smart Healthcare
• IoT in Smart Robotics
• Smart Learning Management System & Technology
• IoT for Blockchain
• Artificial Intelligence in Cloud-based IoT
• Machine Learning for Internet of Things
• Fuzzy Systems for the Internet of Things
• Deep Learning for Internet of Things

Published Papers


  • Open Access

    ARTICLE

    Weber Law Based Approach for Multi-Class Image Forgery Detection

    Arslan Akram, Javed Rashid, Arfan Jaffar, Fahima Hajjej, Waseem Iqbal, Nadeem Sarwar
    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 145-166, 2024, DOI:10.32604/cmc.2023.041074
    (This article belongs to the Special Issue: The Next Generation of Artificial Intelligence and the Intelligent Internet of Things)
    Abstract Today’s forensic science introduces a new research area for digital image analysis for multimedia security. So, Image authentication issues have been raised due to the wide use of image manipulation software to obtain an illegitimate benefit or create misleading publicity by using tempered images. Exiting forgery detection methods can classify only one of the most widely used Copy-Move and splicing forgeries. However, an image can contain one or more types of forgeries. This study has proposed a hybrid method for classifying Copy-Move and splicing images using texture information of images in the spatial domain. Firstly, More >

  • Open Access

    ARTICLE

    Enhanced Steganalysis for Color Images Using Curvelet Features and Support Vector Machine

    Arslan Akram, Imran Khan, Javed Rashid, Mubbashar Saddique, Muhammad Idrees, Yazeed Yasin Ghadi, Abdulmohsen Algarni
    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1311-1328, 2024, DOI:10.32604/cmc.2023.040512
    (This article belongs to the Special Issue: The Next Generation of Artificial Intelligence and the Intelligent Internet of Things)
    Abstract Algorithms for steganography are methods of hiding data transfers in media files. Several machine learning architectures have been presented recently to improve stego image identification performance by using spatial information, and these methods have made it feasible to handle a wide range of problems associated with image analysis. Images with little information or low payload are used by information embedding methods, but the goal of all contemporary research is to employ high-payload images for classification. To address the need for both low- and high-payload images, this work provides a machine-learning approach to steganography image classification… More >

  • Open Access

    ARTICLE

    Intelligent Solution System for Cloud Security Based on Equity Distribution: Model and Algorithms

    Sarah Mustafa Eljack, Mahdi Jemmali, Mohsen Denden, Mutasim Al Sadig, Abdullah M. Algashami, Sadok Turki
    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1461-1479, 2024, DOI:10.32604/cmc.2023.040919
    (This article belongs to the Special Issue: The Next Generation of Artificial Intelligence and the Intelligent Internet of Things)
    Abstract In the cloud environment, ensuring a high level of data security is in high demand. Data planning storage optimization is part of the whole security process in the cloud environment. It enables data security by avoiding the risk of data loss and data overlapping. The development of data flow scheduling approaches in the cloud environment taking security parameters into account is insufficient. In our work, we propose a data scheduling model for the cloud environment. The model is made up of three parts that together help dispatch user data flow to the appropriate cloud VMs.… More >

  • Open Access

    ARTICLE

    A Deep Learning Based Sentiment Analytic Model for the Prediction of Traffic Accidents

    Nadeem Malik, Saud Altaf, Muhammad Usman Tariq, Ashir Ahmed, Muhammad Babar
    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1599-1615, 2023, DOI:10.32604/cmc.2023.040455
    (This article belongs to the Special Issue: The Next Generation of Artificial Intelligence and the Intelligent Internet of Things)
    Abstract The severity of traffic accidents is a serious global concern, particularly in developing nations. Knowing the main causes and contributing circumstances may reduce the severity of traffic accidents. There exist many machine learning models and decision support systems to predict road accidents by using datasets from different social media forums such as Twitter, blogs and Facebook. Although such approaches are popular, there exists an issue of data management and low prediction accuracy. This article presented a deep learning-based sentiment analytic model known as Extra-large Network Bi-directional long short term memory (XLNet-Bi-LSTM) to predict traffic collisions More >

  • Open Access

    ARTICLE

    Energy Efficient and Intelligent Mosquito Repellent Fuzzy Control System

    Aaqib Inam, Zhu Li, Salah-ud-din Khokhar, Zubia Zafar, Muhammad Imran
    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 699-715, 2023, DOI:10.32604/cmc.2023.039707
    (This article belongs to the Special Issue: The Next Generation of Artificial Intelligence and the Intelligent Internet of Things)
    Abstract Mosquitoes are of great concern for occasionally carrying noxious diseases (dengue, malaria, zika, and yellow fever). To control mosquitoes, it is very crucial to effectively monitor their behavioral trends and presence. Traditional mosquito repellent works by heating small pads soaked in repellant, which then diffuses a protected area around you, a great alternative to spraying yourself with insecticide. But they have limitations, including the range, turning them on manually, and then waiting for the protection to kick in when the mosquitoes may find you. This research aims to design a fuzzy-based controller to solve the… More >

  • Open Access

    ARTICLE

    Intelligent Service Search Model Using Emerging Technologies

    Farhan Amin, Gyu Sang Choi
    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1165-1181, 2023, DOI:10.32604/cmc.2023.040693
    (This article belongs to the Special Issue: The Next Generation of Artificial Intelligence and the Intelligent Internet of Things)
    Abstract In recent years, the Internet of Things (IoT) has played a vital role in providing various services to users in a smart city. However, searching for services, objects, data, and frameworks remains a concern. The technological advancements in Cyber-Physical Systems (CPSs) and the Social Internet of Things (SIoT) open a new era of research. Thus, we propose a Cyber-Physical-Social Systems (CPSs) for service search. Herein, service search and object discovery operation carries with the suitable selection of friends in the network. Our proposed model constructs a graph and performs social network analysis (SNA). We suggest More >

  • Open Access

    ARTICLE

    Binary Oriented Feature Selection for Valid Product Derivation in Software Product Line

    Muhammad Fezan Afzal, Imran Khan, Javed Rashid, Mubbashar Saddique, Heba G. Mohamed
    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3653-3670, 2023, DOI:10.32604/cmc.2023.041627
    (This article belongs to the Special Issue: The Next Generation of Artificial Intelligence and the Intelligent Internet of Things)
    Abstract Software Product Line (SPL) is a group of software-intensive systems that share common and variable resources for developing a particular system. The feature model is a tree-type structure used to manage SPL’s common and variable features with their different relations and problem of Crosstree Constraints (CTC). CTC problems exist in groups of common and variable features among the sub-tree of feature models more diverse in Internet of Things (IoT) devices because different Internet devices and protocols are communicated. Therefore, managing the CTC problem to achieve valid product configuration in IoT-based SPL is more complex, time-consuming,… More >

Share Link