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  • 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 - 16 June 2022

    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… More >

  • Open Access

    ARTICLE

    Construction and Optimization of TRNG Based Substitution Boxes for Block Encryption Algorithms

    Muhammad Fahad Khan1,2,*, Khalid Saleem1, Mohammed Alotaibi3, Mohammad Mazyad Hazzazi4, Eid Rehman2, Aaqif Afzaal Abbasi2, Muhammad Asif Gondal5

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2679-2696, 2022, DOI:10.32604/cmc.2022.027655 - 16 June 2022

    Abstract Internet of Things is an ecosystem of interconnected devices that are accessible through the internet. The recent research focuses on adding more smartness and intelligence to these edge devices. This makes them susceptible to various kinds of security threats. These edge devices rely on cryptographic techniques to encrypt the pre-processed data collected from the sensors deployed in the field. In this regard, block cipher has been one of the most reliable options through which data security is accomplished. The strength of block encryption algorithms against different attacks is dependent on its nonlinear primitive which is… More >

  • Open Access

    REVIEW

    Recent Progress in Cellulose-Based Flexible Sensors

    Ningli An1, Jingxuan Qin1, Xing Zhou1, Quandai Wang2, Changqing Fang1,*, Jiapeng Guo2, Bin Nan2

    Journal of Renewable Materials, Vol.10, No.9, pp. 2319-2334, 2022, DOI:10.32604/jrm.2022.021030 - 30 May 2022

    Abstract Flexible sensors are attractive due to potential applications in body exercise and ambient gas monitoring systems. Cellulose and its derivatives have combined superiorities such as intrinsic and structural flexibility, ease of chemical functionalization, moisture sensitivity, and mechanical stability, enabling them to be promising candidates as flexible supporting substrates and flexible sensitive materials. Significant progress consequently has been achieved to improve mechanical, electrical, and chemical performance. The latest advance in materials synthesis, structure design, fabrication control, and working mechanism of novel cellulose-based flexible sensors are reviewed and discussed, including strain sensors, humidity sensors, and harmful gas More > Graphic Abstract

    Recent Progress in Cellulose-Based Flexible Sensors

  • Open Access

    ARTICLE

    Sport-Related Activity Recognition from Wearable Sensors Using Bidirectional GRU Network

    Sakorn Mekruksavanich1, Anuchit Jitpattanakul2,*

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1907-1925, 2022, DOI:10.32604/iasc.2022.027233 - 25 May 2022

    Abstract Numerous learning-based techniques for effective human activity recognition (HAR) have recently been developed. Wearable inertial sensors are critical for HAR studies to characterize sport-related activities. Smart wearables are now ubiquitous and can benefit people of all ages. HAR investigations typically involve sensor-based evaluation. Sport-related activities are unpredictable and have historically been classified as complex, with conventional machine learning (ML) algorithms applied to resolve HAR issues. The efficiency of machine learning techniques in categorizing data is limited by the human-crafted feature extraction procedure. A deep learning model named MBiGRU (multimodal bidirectional gated recurrent unit) neural network More >

  • Open Access

    ARTICLE

    MagneFi: Multiuser, Multi-Building and Multi-Floor Geomagnetic Field Dataset for Indoor Positioning

    Imran Ashraf1, Muhammad Usman Ali2, Soojung Hur1, Gunzung Kim1, Yongwan Park1,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1747-1768, 2022, DOI:10.32604/cmc.2022.020610 - 18 May 2022

    Abstract Indoor positioning and localization have emerged as a potential research area during the last few years owing to the wide proliferation of smartphones and the inception of location-attached services for the consumer industry. Due to the importance of precise location information, several positioning technologies are adopted such as Wi-Fi, ultrawideband, infrared, radio frequency identification, Bluetooth beacons, pedestrian dead reckoning, and magnetic field, etc. Although Wi-Fi and magnetic field-based positioning are more attractive concerning the deployment of Wi-Fi access points and ubiquity of magnetic field data, the latter is preferred as it does not require any… More >

  • Open Access

    ARTICLE

    Low-Cost IMU Sensors for Satellite Maturity Improvement

    Omar Ben Bahri*, Abdullah Alhumaidi Alotaibi

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1315-1326, 2022, DOI:10.32604/csse.2022.024979 - 09 May 2022

    Abstract The satellite technology proves its impact in the modern era with its wide benefits and applications. However, the cost of the development in this field presents gaps in many countries, almost the developed countries. Therefore, this paper provides a rich platform around low-cost sensors in order to improve maturity in space technology, mostly the system of attitude determination and control. The development of this knowledge turns out to be very interesting in order to achieve a space mission which leads to the progression of the spatial technology readiness level (TRL) defined by the international measurement More >

  • Open Access

    ARTICLE

    Smartphone Sensors Based Physical Life-Routine for Health Education

    Tamara al Shloul1, Usman Azmat2, Suliman A. Alsuhibany3, Yazeed Yasin Ghadi4, Ahmad Jalal2, Jeongmin Park5,*

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 715-732, 2022, DOI:10.32604/iasc.2022.025421 - 03 May 2022

    Abstract The physical and the mental health of a human being largely depends upon his physical life-routine (PLR) and today’s much advanced technological methods make it possible to recognize and keep track of an individual’s PLR. With the successful and accurate recognition of PLR, a sublime service of health education can be made copious. In this regard, smartphones can play a vital role as they are ubiquitous and have utilitarian sensors embedded in them. In this paper, we propose a framework that extracts the features from the smartphone sensors data and then uses the sequential feature… More >

  • Open Access

    ARTICLE

    Object Detection Learning for Intelligent Self Automated Vehicles

    Ahtsham Alam1, Syed Ahmed Abdullah1, Israr Akhter1, Suliman A. Alsuhibany2,*, Yazeed Yasin Ghadi3, Tamara al Shloul4, Ahmad Jalal1

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 941-955, 2022, DOI:10.32604/iasc.2022.024840 - 03 May 2022

    Abstract Robotics is a part of today's communication that makes human life simpler in the day-to-day aspect. Therefore, we are supporting this cause by making a smart city project that is based on Artificial Intelligence, image processing, and some touch of hardware such as robotics. In particular, we advocate a self automation device (i.e., autonomous car) that performs actions and takes choices on its very own intelligence with the assist of sensors. Sensors are key additives for developing and upgrading all forms of self-sustaining cars considering they could offer the information required to understand the encircling… More >

  • Open Access

    ARTICLE

    An Interpretable Artificial Intelligence Based Smart Agriculture System

    Fariza Sabrina1,*, Shaleeza Sohail2, Farnaz Farid3, Sayka Jahan4, Farhad Ahamed5, Steven Gordon6

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3777-3797, 2022, DOI:10.32604/cmc.2022.026363 - 29 March 2022

    Abstract With increasing world population the demand of food production has increased exponentially. Internet of Things (IoT) based smart agriculture system can play a vital role in optimising crop yield by managing crop requirements in real-time. Interpretability can be an important factor to make such systems trusted and easily adopted by farmers. In this paper, we propose a novel artificial intelligence-based agriculture system that uses IoT data to monitor the environment and alerts farmers to take the required actions for maintaining ideal conditions for crop production. The strength of the proposed system is in its interpretability… More >

  • Open Access

    ARTICLE

    Fault Pattern Diagnosis and Classification in Sensor Nodes Using Fall Curve

    Mudita Uppal1, Deepali Gupta1, Divya Anand2, Fahd S. Alharithi3, Jasem Almotiri3, Arturo Mansilla4,5, Dinesh Singh6, Nitin Goyal1,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1799-1814, 2022, DOI:10.32604/cmc.2022.025330 - 24 February 2022

    Abstract The rapid expansion of Internet of Things (IoT) devices deploys various sensors in different applications like homes, cities and offices. IoT applications depend upon the accuracy of sensor data. So, it is necessary to predict faults in the sensor and isolate their cause. A novel primitive technique named fall curve is presented in this paper which characterizes sensor faults. This technique identifies the faulty sensor and determines the correct working of the sensor. Different sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in IoT devices are… More >

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