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  • Open Access

    ARTICLE

    Healthcare Monitoring Using Ensemble Classifiers in Fog Computing Framework

    P. M. Arunkumar1, Mehedi Masud2, Sultan Aljahdali2, Mohamed Abouhawwash3,4,*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2265-2280, 2023, DOI:10.32604/csse.2023.032571

    Abstract Nowadays, the cloud environment faces numerous issues like synchronizing information before the switch over the data migration. The requirement for a centralized internet of things (IoT)-based system has been restricted to some extent. Due to low scalability on security considerations, the cloud seems uninteresting. Since healthcare networks demand computer operations on large amounts of data, the sensitivity of device latency evolved among health networks is a challenging issue. In comparison to cloud domains, the new paradigms of fog computing give fresh alternatives by bringing resources closer to users by providing low latency and energy-efficient data processing solutions. Previous fog computing… More >

  • Open Access

    ARTICLE

    Development of IoT-Based Condition Monitoring System for Bridges

    Sheetal A. Singh, Suresh S. Balpande*

    Sound & Vibration, Vol.56, No.3, pp. 209-220, 2022, DOI:10.32604/sv.2022.014518

    Abstract As of April 2019, India has 1,42,126 kilometres of National Highways and 67,368 kilometres of railway tracks that reach even the most remote parts of the country. Bridges are critical for both passenger and freight movement in the country. Because bridges play such an important part in the transportation system, their safety and upkeep must be prioritized. Manual Condition Monitoring has the disadvantage of being sluggish, unreliable, and ineffi- cient. The Internet of Things has given structural monitoring a boost. Significant decreases in the cost of electronics and connection, together with the expansion of cloud platforms, have made it possible… More >

  • Open Access

    ARTICLE

    Data Reliability and Sensors Lifetime in Bridge Health Monitoring using LoRaWAN-Zigbee

    Awad Ali1,*, Reyazur Rashid Irshad1, Ahmed Abdu Alattaab1, Aamir Fatahayab2

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2663-2678, 2022, DOI:10.32604/cmc.2022.028503

    Abstract The Wireless Sensor Network (WSN) is regarded as the fastest expanding technological trend in recent years due its application in a variety of sectors. In the monitoring region, several sensor nodes with various sensing capabilities are installed to gather appropriate data and communicate it to the gateway. The proposed system of the heterogeneous WSN employing LoRaWAN-Zigbee based hybrid communication is explored in this research study. To communicate in a network, two Long–Range Wide Area Network (LoRaWAN) sensor clusters and two Zigbee sensor clusters are employed, together with two Zigbee and LoRaWAN converters. The suggested Golden eagle shepherd optimization (GESO) method… More >

  • Open Access

    ARTICLE

    A Smart Room to Promote Autonomy of Disabled People due to Stroke

    Moeiz Miraoui1,2,*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 677-692, 2023, DOI:10.32604/csse.2023.025799

    Abstract A cerebral vascular accident, known as common language stroke, is one of the main causes of mortality and remains the primary cause of acquired disabilities in adults. Those disabled people spend most of their time at home in their living rooms. In most cases, appliances of a living room (TV, light, cooler/heater, window blinds, etc.) are generally controlled by direct manipulation of a set of remote controls. Handling many remote controls can be disturbing and inappropriate for these people. In addition, in many cases these people could be alone at home and must open the door for visitors after their… More >

  • Open Access

    ARTICLE

    Neural Cryptography with Fog Computing Network for Health Monitoring Using IoMT

    G. Ravikumar1, K. Venkatachalam2, Mohammed A. AlZain3, Mehedi Masud4, Mohamed Abouhawwash5,6,*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 945-959, 2023, DOI:10.32604/csse.2023.024605

    Abstract Sleep apnea syndrome (SAS) is a breathing disorder while a person is asleep. The traditional method for examining SAS is Polysomnography (PSG). The standard procedure of PSG requires complete overnight observation in a laboratory. PSG typically provides accurate results, but it is expensive and time consuming. However, for people with Sleep apnea (SA), available beds and laboratories are limited. Resultantly, it may produce inaccurate diagnosis. Thus, this paper proposes the Internet of Medical Things (IoMT) framework with a machine learning concept of fully connected neural network (FCNN) with k-nearest neighbor (k-NN) classifier. This paper describes smart monitoring of a patient’s… More >

  • Open Access

    ARTICLE

    IoT Based Disease Prediction Using Mapreduce and LSQN3 Techniques

    R. Gopi1,*, S. Veena2, S. Balasubramanian3, D. Ramya4, P. Ilanchezhian5, A. Harshavardhan6, Zatin Gupta7

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1215-1230, 2022, DOI:10.32604/iasc.2022.025792

    Abstract In this modern era, the transformation of conventional objects into smart ones via internet vitality, data management, together with many more are the main aim of the Internet of Things (IoT) centered Big Data (BD) analysis. In the past few years, significant augmentation in the IoT-centered Healthcare (HC) monitoring can be seen. Nevertheless, the merging of health-specific parameters along with IoT-centric Health Monitoring (HM) systems with BD handling ability is turned out to be a complicated research scope. With the aid of Map-Reduce and LSQN3 techniques, this paper proposed IoT devices in Wireless Sensors Networks (WSN) centered BD Mining (BDM)… More >

  • Open Access

    REVIEW

    Review Article on Condition Assessment of Structures Using Electro-Mechanical Impedance Technique

    Krishna Kumar Maurya*, Anupam Rawat, Rama Shanker

    Structural Durability & Health Monitoring, Vol.16, No.2, pp. 97-128, 2022, DOI:10.32604/sdhm.2022.015732

    Abstract Structural health monitoring (SHM) is a process for determination of presence, location, severity of damages and remaining life of the infrastructures. SHM is widely applied in aerospace, mechanical and civil engineering systems to assess the conditions of structures to improve the operation, safety, serviceability and reliability, respectively. There are various SHM techniques for monitoring the health of structures such as global response based and local techniques. Damages occur in the structures due to its inability to withstand intended design loadings, physical environment and chemical environment. Therefore, damage identification is necessary to improve the durability of the structures for protection against… More >

  • Open Access

    ARTICLE

    Intelligent Cloud IoMT Health Monitoring-Based System for COVID-19

    Hameed AlQaheri1,*, Manash Sarkar2, Saptarshi Gupta3, Bhavya Gaur4

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 497-517, 2022, DOI:10.32604/cmc.2022.022735

    Abstract The most common alarming and dangerous disease in the world today is the coronavirus disease 2019 (COVID-19). The coronavirus is perceived as a group of coronaviruses which causes mild to severe respiratory diseases among human beings. The infection is spread by aerosols emitted from infected individuals during talking, sneezing, and coughing. Furthermore, infection can occur by touching a contaminated surface followed by transfer of the viral load to the face. Transmission may occur through aerosols that stay suspended in the air for extended periods of time in enclosed spaces. To stop the spread of the pandemic, it is crucial to… More >

  • Open Access

    ARTICLE

    Shape Sensing of Thin Shell Structure Based on Inverse Finite Element Method

    Zhanjun Wu1, Tengteng Li1, Jiachen Zhang2, Yifan Wu3, Jianle Li1, Lei Yang1, Hao Xu1,*

    Structural Durability & Health Monitoring, Vol.16, No.1, pp. 1-14, 2022, DOI:10.32604/sdhm.2022.019554

    Abstract Shape sensing as a crucial component of structural health monitoring plays a vital role in real-time actuation and control of smart structures, and monitoring of structural integrity. As a model-based method, the inverse finite element method (iFEM) has been proved to be a valuable shape sensing tool that is suitable for complex structures. In this paper, we propose a novel approach for the shape sensing of thin shell structures with iFEM. Considering the structural form and stress characteristics of thin-walled structure, the error function consists of membrane and bending section strains only which is consistent with the Kirchhoff–Love shell theory.… More >

  • Open Access

    ARTICLE

    Aluminum Alloy Fatigue Crack Damage Prediction Based on Lamb Wave-Systematic Resampling Particle Filter Method

    Gaozheng Zhao1, Changchao Liu1, Lingyu Sun1, Ning Yang2, Lei Zhang1, Mingshun Jiang1, Lei Jia1, Qingmei Sui1,*

    Structural Durability & Health Monitoring, Vol.16, No.1, pp. 81-96, 2022, DOI:10.32604/sdhm.2022.016905

    Abstract Fatigue crack prediction is a critical aspect of prognostics and health management research. The particle filter algorithm based on Lamb wave is a potential tool to solve the nonlinear and non-Gaussian problems on fatigue growth, and it is widely used to predict the state of fatigue crack. This paper proposes a method of lamb wave-based early fatigue microcrack prediction with the aid of particle filters. With this method, which the changes in signal characteristics under different fatigue crack lengths are analyzed, and the state- and observation-equations of crack extension are established. Furthermore, an experiment is conducted to verify the feasibility… More >

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