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  • Open Access

    ARTICLE

    An Efficient ResNetSE Architecture for Smoking Activity Recognition from Smartwatch

    Narit Hnoohom1, Sakorn Mekruksavanich2, Anuchit Jitpattanakul3,4,*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1245-1259, 2023, DOI:10.32604/iasc.2023.028290

    Abstract Smoking is a major cause of cancer, heart disease and other afflictions that lead to early mortality. An effective smoking classification mechanism that provides insights into individual smoking habits would assist in implementing addiction treatment initiatives. Smoking activities often accompany other activities such as drinking or eating. Consequently, smoking activity recognition can be a challenging topic in human activity recognition (HAR). A deep learning framework for smoking activity recognition (SAR) employing smartwatch sensors was proposed together with a deep residual network combined with squeeze-and-excitation modules (ResNetSE) to increase the effectiveness of the SAR framework. The proposed model was tested against… More >

  • Open Access

    ARTICLE

    Smart Devices Based Multisensory Approach for Complex Human Activity Recognition

    Muhammad Atif Hanif1, Tallha Akram1, Aamir Shahzad2, Muhammad Attique Khan3, Usman Tariq4, Jung-In Choi5, Yunyoung Nam6,*, Zanib Zulfiqar7

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3221-3234, 2022, DOI:10.32604/cmc.2022.019815

    Abstract Sensors based Human Activity Recognition (HAR) have numerous applications in eHeath, sports, fitness assessments, ambient assisted living (AAL), human-computer interaction and many more. The human physical activity can be monitored by using wearable sensors or external devices. The usage of external devices has disadvantages in terms of cost, hardware installation, storage, computational time and lighting conditions dependencies. Therefore, most of the researchers used smart devices like smart phones, smart bands and watches which contain various sensors like accelerometer, gyroscope, GPS etc., and adequate processing capabilities. For the task of recognition, human activities can be broadly categorized as basic and complex… More >

  • Open Access

    ARTICLE

    Motion-Based Activities Monitoring through Biometric Sensors Using Genetic Algorithm

    Mohammed Alshehri1,*, Purushottam Sharma2, Richa Sharma2, Osama Alfarraj3

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2525-2538, 2021, DOI:10.32604/cmc.2021.012469

    Abstract Sensors and physical activity evaluation are quite limited for motion-based commercial devices. Sometimes the accelerometer of the smartwatch is utilized; walking is investigated. The combination can perform better in terms of sensors and that can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated, also with biometric authentication. The result shows that using the different computing techniques in phones and watch for biometric can provide a suitable output based on the mentioned activities. This indicates that the high feasibility and results… More >

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