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  • Open Access

    ARTICLE

    Efficient Computation Offloading of IoT-Based Workflows Using Discrete Teaching Learning-Based Optimization

    Mohamed K. Hussein1,*, Mohamed H. Mousa1,2

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3685-3703, 2022, DOI:10.32604/cmc.2022.026370

    Abstract As the Internet of Things (IoT) and mobile devices have rapidly proliferated, their computationally intensive applications have developed into complex, concurrent IoT-based workflows involving multiple interdependent tasks. By exploiting its low latency and high bandwidth, mobile edge computing (MEC) has emerged to achieve the high-performance computation offloading of these applications to satisfy the quality-of-service requirements of workflows and devices. In this study, we propose an offloading strategy for IoT-based workflows in a high-performance MEC environment. The proposed task-based offloading strategy consists of an optimization problem that includes task dependency, communication costs, workflow constraints, device energy consumption, and the heterogeneous characteristics… More >

  • Open Access

    ARTICLE

    Novel Block Chain Technique for Data Privacy and Access Anonymity in Smart Healthcare

    J. Priya*, C. Palanisamy

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 243-259, 2023, DOI:10.32604/iasc.2023.025719

    Abstract The Internet of Things (IoT) and Cloud computing are gaining popularity due to their numerous advantages, including the efficient utilization of internet and computing resources. In recent years, many more IoT applications have been extensively used. For instance, Healthcare applications execute computations utilizing the user’s private data stored on cloud servers. However, the main obstacles faced by the extensive acceptance and usage of these emerging technologies are security and privacy. Moreover, many healthcare data management system applications have emerged, offering solutions for distinct circumstances. But still, the existing system has issues with specific security issues, privacy-preserving rate, information loss, etc.… More >

  • Open Access

    ARTICLE

    Anomaly Detection Framework in Fog-to-Things Communication for Industrial Internet of Things

    Tahani Alatawi*, Ahamed Aljuhani

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1067-1086, 2022, DOI:10.32604/cmc.2022.029283

    Abstract The rapid development of the Internet of Things (IoT) in the industrial domain has led to the new term the Industrial Internet of Things (IIoT). The IIoT includes several devices, applications, and services that connect the physical and virtual space in order to provide smart, cost-effective, and scalable systems. Although the IIoT has been deployed and integrated into a wide range of industrial control systems, preserving security and privacy of such a technology remains a big challenge. An anomaly-based Intrusion Detection System (IDS) can be an effective security solution for maintaining the confidentiality, integrity, and availability of data transmitted in… More >

  • Open Access

    ARTICLE

    Deep Reinforcement Extreme Learning Machines for Secured Routing in Internet of Things (IoT) Applications

    K. Lavanya1,*, K. Vimala Devi2, B. R. Tapas Bapu3

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 837-848, 2022, DOI:10.32604/iasc.2022.023055

    Abstract Multipath TCP (SMPTCP) has gained more attention as a valuable approach for IoT systems. SMPTCP is introduced as an evolution of Transmission Control Protocol (TCP) to pass packets simultaneously across several routes to completely exploit virtual networks on multi-homed consoles and other network services. The current multipath networking algorithms and simulation software strategies are confronted with sub-flow irregularity issues due to network heterogeneity, and routing configuration issues can be fixed adequately. To overcome the issues, this paper proposes a novel deep reinforcement-based extreme learning machines (DRLELM) approach to examine the complexities between routes, pathways, sub-flows, and SMPTCP connections in different… More >

  • Open Access

    ARTICLE

    Blockchain-Based Robust Data Security Scheme in IoT-Enabled Smart Home

    Anusha Vangala1, Ashok Kumar Das1, YoungHo Park2,*, Sajjad Shaukat Jamal3

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3549-3570, 2022, DOI:10.32604/cmc.2022.025660

    Abstract The recent surge in development of smart homes and smart cities can be observed in many developed countries. While the idea to control devices that are in home (embedded with the Internet of Things (IoT) smart devices) by the user who is outside the home might sound fancy, but it comes with a lot of potential threats. There can be many attackers who will be trying to take advantage of this. So, there is a need for designing a secure scheme which will be able to distinguish among genuine/authorized users of the system and attackers. And knowing about the details… More >

  • Open Access

    ARTICLE

    IoT and Blockchain-Based Mask Surveillance System for COVID-19 Prevention Using Deep Learning

    Wahidur Rahman1, Naif Al Mudawi2,*, Abdulwahab Alazeb2, Muhammad Minoar Hossain1, Saima Siddique Tashfia1, Md. Tarequl Islam1, Shisir Mia1, Mohammad Motiur Rahman1

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 2033-2053, 2022, DOI:10.32604/cmc.2022.025025

    Abstract On the edge of the worldwide public health crisis, the COVID-19 disease has become a serious headache for its destructive nature on humanity worldwide. Wearing a facial mask can be an effective possible solution to mitigate the spreading of the virus and reduce the death rate. Thus, wearing a face mask in public places such as shopping malls, hotels, restaurants, homes, and offices needs to be enforced. This research work comes up with a solution of mask surveillance system utilizing the mechanism of modern computations like Deep Learning (DL), Internet of things (IoT), and Blockchain. The absence or displacement of… More >

  • Open Access

    ARTICLE

    Anomaly Detection for Internet of Things Cyberattacks

    Manal Alanazi*, Ahamed Aljuhani

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 261-279, 2022, DOI:10.32604/cmc.2022.024496

    Abstract The Internet of Things (IoT) has been deployed in diverse critical sectors with the aim of improving quality of service and facilitating human lives. The IoT revolution has redefined digital services in different domains by improving efficiency, productivity, and cost-effectiveness. Many service providers have adapted IoT systems or plan to integrate them as integral parts of their systems’ operation; however, IoT security issues remain a significant challenge. To minimize the risk of cyberattacks on IoT networks, anomaly detection based on machine learning can be an effective security solution to overcome a wide range of IoT cyberattacks. Although various detection techniques… More >

  • Open Access

    ARTICLE

    A Wireless ECG Monitoring and Analysis System Using the IoT Cloud

    Anas Bushnag*

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 51-70, 2022, DOI:10.32604/iasc.2022.024005

    Abstract A portable electrocardiogram (ECG) monitoring system is essential for elderly and remote patients who are not able to visit the hospital regularly. The system connects a patient to his/her doctor through an Internet of Things (IoT) cloud server that provides all the information needed to diagnose heart diseases. Patients use an ECG monitoring device to collect and upload information regarding their current medical situation via the Message Queue Telemetry Transport (MQTT) protocol to the server. The IoT cloud server performs further analysis that can be useful for both the doctor and the patient. Moreover, the proposed system has an alert… More >

  • Open Access

    ARTICLE

    Automated Identification Algorithm Using CNN for Computer Vision in Smart Refrigerators

    Pulkit Jain1, Paras Chawla1, Mehedi Masud2,*, Shubham Mahajan3, Amit Kant Pandit3

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3337-3353, 2022, DOI:10.32604/cmc.2022.023053

    Abstract Machine Learning has evolved with a variety of algorithms to enable state-of-the-art computer vision applications. In particular the need for automating the process of real-time food item identification, there is a huge surge of research so as to make smarter refrigerators. According to a survey by the Food and Agriculture Organization of the United Nations (FAO), it has been found that 1.3 billion tons of food is wasted by consumers around the world due to either food spoilage or expiry and a large amount of food is wasted from homes and restaurants itself. Smart refrigerators have been very successful in… 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

    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 (0°, 45°, and 90°) of… More >

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