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  • Open Access

    ARTICLE

    Digital Object Architecture for IoT Networks

    Mahmood Al-Bahri1, Abdelhamied Ateya2,3, Ammar Muthanna3, Abeer D. Algarni4, Naglaa F. Soliman4,*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 97-110, 2023, DOI:10.32604/iasc.2023.026115 - 06 June 2022

    Abstract The Internet of Things (IoT) is a recent technology, which implies the union of objects, “things”, into a single worldwide network. This promising paradigm faces many design challenges associated with the dramatic increase in the number of end-devices. Device identification is one of these challenges that becomes complicated with the increase of network devices. Despite this, there is still no universally accepted method of identifying things that would satisfy all requirements of the existing IoT devices and applications. In this regard, one of the most important problems is choosing an identification system for all IoT… 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 - 06 June 2022

    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,… More >

  • Open Access

    ARTICLE

    Novel Sensing Hole Recovery with Expanded Relay Node Capability

    Moonseong Kim1, Woochan Lee2,*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 663-675, 2023, DOI:10.32604/csse.2023.025615 - 01 June 2022

    Abstract The occurrence of ‘sensing holes’ not only hinders seamless data collection but also leads to misinterpretation of information in certain areas under extensive data analysis. In order to overcome this, various sensor relocation strategies have been proposed, but the existing relocation strategies revealed problems such as the ping-pong, shaded area, network disconnection, etc. This paper conducted research on relocation protocols in a distributed environment that is very suitable for real-world situations and efficiently recovering the problem of sensing holes. First, a simulation was performed on the distribution of the shaded area for data collection, which More >

  • Open Access

    ARTICLE

    Energy Aware Clustering with Medical Data Classification Model in IoT Environment

    R. Bharathi1,*, T. Abirami2

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 797-811, 2023, DOI:10.32604/csse.2023.025336 - 01 June 2022

    Abstract With the exponential developments of wireless networking and inexpensive Internet of Things (IoT), a wide range of applications has been designed to attain enhanced services. Due to the limited energy capacity of IoT devices, energy-aware clustering techniques can be highly preferable. At the same time, artificial intelligence (AI) techniques can be applied to perform appropriate disease diagnostic processes. With this motivation, this study designs a novel squirrel search algorithm-based energy-aware clustering with a medical data classification (SSAC-MDC) model in an IoT environment. The goal of the SSAC-MDC technique is to attain maximum energy efficiency and… More >

  • Open Access

    REVIEW

    Quality of Experience in Internet of Things: A Systematic Literature Review

    Rawan Sanyour*, Manal Abdullah, Salha Abdullah

    Journal on Internet of Things, Vol.4, No.4, pp. 263-282, 2022, DOI:10.32604/jiot.2022.040966 - 18 July 2023

    Abstract With the rapid growth of the Internet of Things paradigm, a tremendous number of applications and services that require minimal or no human involvement have been developed to enhance the quality of everyday life in various domains. In order to ensure that such services provide their functionalities with the expected quality, it is essential to measure and evaluate this quality, which can be in some cases a challenging task due to the lack of human intervention and feedback. Recently, the vast majority of the Quality of Experience QoE works mainly address the multimedia services. However,… More >

  • Open Access

    ARTICLE

    Real Time Vehicle Status Monitoring under Moving Conditions Using a Low Power IoT System

    M. Vlachos1,*, R. Lopardo2, A. Amditis1

    Journal on Internet of Things, Vol.4, No.4, pp. 235-261, 2022, DOI:10.32604/jiot.2022.040820 - 18 July 2023

    Abstract In the era of the Internet of Things (IoT), the ever-increasing number of devices connected to the IoT networks also increases the energy consumption on the edge. This is prohibitive since the devices living on the edge are generally resource constrained devices in terms of energy consumption and computational power. Thus, trying to tackle this issue, in this paper, a fully automated end-to-end IoT system for real time monitoring of the status of a moving vehicle is proposed. The IoT system consists mainly of three components: (1) the ultra-low power consumption Wireless Sensor Node (WSN),… More >

  • Open Access

    ARTICLE

    Evidence-Based Federated Learning for Set-Valued Classification of Industrial IoT DDos Attack Traffic

    Jiale Cheng1, Zilong Jin1,2,*

    Journal on Internet of Things, Vol.4, No.3, pp. 183-195, 2022, DOI:10.32604/jiot.2022.042054 - 12 June 2023

    Abstract A novel Federated learning classifier is proposed using the Dempster-Shafer (DS) theory for the set-valued classification of industrial IoT Distributed Denial of Service (DDoS) attack traffic. The proposed classifier, referred to as the evidence-based federated learning classifier, employs convolution and pooling layers to extract high-dimensional features of Distributed Denial of Service (DDoS) traffic from the local data of private industrial clients. The characteristics obtained from the various participants are transformed into mass functions and amalgamated utilizing Dempster’s rule within the DS layer, situated on the federated server. Lastly, the set value classification task of attack More >

  • Open Access

    ARTICLE

    A Detailed Study on IoT Platform for ECG Monitoring Using Transfer Learning

    Md Saidul Islam*

    Journal on Internet of Things, Vol.4, No.3, pp. 127-140, 2022, DOI:10.32604/jiot.2022.037489 - 12 June 2023

    Abstract Internet of Things (IoT) technologies used in health have the potential to address systemic difficulties by offering tools for cost reduction while improving diagnostic and treatment efficiency. Numerous works on this subject focus on clarifying the constructs and interfaces between various components of an IoT platform, such as knowledge generation via smart sensors collecting biosignals from the human body and processing them via data mining and, in recent times, deep neural networks offered to host on cloud computing architecture. These approaches are intended to assist healthcare professionals in their daily activities. In this comparative research, More >

  • Open Access

    ARTICLE

    Intrusion Detection Method Based on Active Incremental Learning in Industrial Internet of Things Environment

    Zeyong Sun1, Guo Ran2, Zilong Jin1,3,*

    Journal on Internet of Things, Vol.4, No.2, pp. 99-111, 2022, DOI:10.32604/jiot.2022.037416 - 28 March 2023

    Abstract Intrusion detection is a hot field in the direction of network security. Classical intrusion detection systems are usually based on supervised machine learning models. These offline-trained models usually have better performance in the initial stages of system construction. However, due to the diversity and rapid development of intrusion techniques, the trained models are often difficult to detect new attacks. In addition, very little noisy data in the training process often has a considerable impact on the performance of the intrusion detection system. This paper proposes an intrusion detection system based on active incremental learning with… More >

  • Open Access

    ARTICLE

    Application of Internet of Things Technology in Enterprise Marketing Management Innovation

    Huan Xu1, Sixuan Chen2,*

    Journal on Internet of Things, Vol.4, No.2, pp. 75-84, 2022, DOI:10.32604/jiot.2022.030610 - 28 March 2023

    Abstract Marketing is a very important part of an enterprise. A rational and scientific marketing management can not only reduce the cost of enterprise sales, but also greatly improve the competitiveness of enterprises. The purpose of this paper is to study the innovative application of enterprise marketing management based on the Internet of Things technology. The most suitable competitive strategy of the company is put forward as the centralized strategy. And put forward the clear strategy implementation details, introduced the current situation and history of the Internet of things, and combined with the development status, put… More >

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