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  • Open Access


    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


    A New Intelligent Approach for Deaf/Dumb People based on Deep Learning

    Haitham Elwahsh1,*, Ahmed Elkhouly1, Emad Abouel Nasr2, Ali K. Kamrani3, Engy El-shafeiy4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6045-6060, 2022, DOI:10.32604/cmc.2022.026309


    People who are deaf or have difficulty speaking use sign language, which consists of hand gestures with particular motions that symbolize the “language” they are communicating. A gesture in a sign language is a particular movement of the hands with a specific shape from the fingers and whole hand. In this paper, we present an Intelligent for Deaf/Dumb People approach in real time based on Deep Learning using Gloves (IDLG). The approach IDLG offers scientific contributions based deep-learning, a multi-mode command techniques, real-time, and effective use, and high accuracy rates. For this purpose, smart gloves working in real time were… More >

  • Open Access


    Multi-Floor Indoor Trajectory Reconstruction Using Mobile Devices

    Sultan Alamri1,*, Kartini Nurfalah2, Kiki Adhinugraha3

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 927-948, 2021, DOI:10.32604/cmes.2021.014852

    Abstract An indoor trajectory is the path of an object moving through corridors and stairs inside a building. There are various types of technologies that can be used to reconstruct the path of a moving object and detect its position. GPS has been used for reconstruction in outdoor environments, but for indoor environments, mobile devices with embedded sensors are used. An accelerometer sensor and a magnetometer sensor are used to detect human movement and reconstruct the trajectory on a single floor. In an indoor environment, there are many activities that will create the trajectory similar to an outdoor environment, such as… More >

  • Open Access


    Driving Style Recognition System Using Smartphone Sensors Based on Fuzzy Logic

    Nidhi Kalra1,*, Raman Kumar Goyal1, Anshu Parashar1, Jaskirat Singh1, Gagan Singla2

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1967-1978, 2021, DOI:10.32604/cmc.2021.018732

    Abstract Every 24 seconds, someone dies on the road due to road accidents and it is the 8th leading cause of death and the first among children aged 15–29 years. 1.35 million people globally die every year due to road traffic crashes. An additional 20–50 million suffer from non-fatal injuries, often resulting in long-term disabilities. This costs around 3% of Gross Domestic Product to most countries, and it is a considerable economic loss. The governments have taken various measures such as better road infrastructures and strict enforcement of motor-vehicle laws to reduce these accidents. However, there is still no remarkable reduction… More >

  • Open Access


    Feature Selection for Activity Recognition from Smartphone Accelerometer Data

    Juan C. Quiroza, Amit Banerjeeb, Sergiu M. Dascaluc, Sian Lun Laua

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 785-793, 2018, DOI:10.1080/10798587.2017.1342400

    Abstract We use the public Human Activity Recognition Using Smartphones (HARUS) data-set to investigate and identify the most informative features for determining the physical activity performed by a user based on smartphone accelerometer and gyroscope data. The HARUS data-set includes 561 time domain and frequency domain features extracted from sensor readings collected from a smartphone carried by 30 users while performing specific activities. We compare the performance of a decision tree, support vector machines, Naive Bayes, multilayer perceptron, and bagging. We report the various classification performances of these algorithms for subject independent cases. Our results show that bagging and the multilayer… More >

  • Open Access


    A Survey of Error Analysis and Calibration Methods for MEMS Triaxial Accelerometers

    Bo Xiao1, Yinghang Jiang2, Qi Liu2, 5, *, Xiaodong Liu3, Mingxu Sun4, *

    CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 389-399, 2020, DOI:10.32604/cmc.2020.06092

    Abstract MEMS accelerometers are widely used in various fields due to their small size and low cost, and have good application prospects. However, the low accuracy limits its range of applications. To ensure data accuracy and safety we need to calibrate MEMS accelerometers. Many authors have improved accelerometer accuracy by calculating calibration parameters, and a large number of published calibration methods have been confusing. In this context, this paper introduces these techniques and methods, analyzes and summarizes the main error models and calibration procedures, and provides useful suggestions. Finally, the content of the accelerometer calibration method needs to be overcome. More >

  • Open Access


    Classifying Machine Learning Features Extracted from Vibration Signal with Logistic Model Tree to Monitor Automobile Tyre Pressure

    P. S. Anoop1, V. Sugumaran2

    Structural Durability & Health Monitoring, Vol.11, No.2, pp. 191-208, 2017, DOI:10.3970/sdhm.2017.011.191

    Abstract Tyre pressure monitoring system (TPMS) is compulsory in most countries like the United States and European Union. The existing systems depend on pressure sensors strapped on the tyre or on wheel speed sensor data. A difference in wheel speed would trigger an alarm based on the algorithm implemented. In this paper, machine learning approach is proposed as a new method to monitor tyre pressure by extracting the vertical vibrations from a wheel hub of a moving vehicle using an accelerometer. The obtained signals will be used to compute through statistical features and histogram features for the feature extraction process. The… More >

  • Open Access


    An Auto-Calibration Approach to Robust and Secure Usage of Accelerometers for Human Motion Analysis in FES Therapies

    Mingxu Sun1,#,*, Yinghang Jiang2,3,#, Qi Liu3,4,*, Xiaodong Liu4

    CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 67-83, 2019, DOI:10.32604/cmc.2019.06079

    Abstract A Functional Electrical stimulation (FES) therapy is a common rehabilitation intervention after stroke, and finite state machine (FSM) has proven to be an effective and intuitive FES control method. The FSM uses the data information generated by the accelerometer to robustly trigger state transitions. In the medical field, it is necessary to obtain highly safe and accurate acceleration data. In order to ensure the accuracy of the acceleration sensor data without affecting the accuracy of the motion analysis, we need to perform acceleration big data calibration. In this context, we propose a method for robustly calculating the auto-calibration gain using… More >

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