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  • Open Access

    ARTICLE

    An IoT-Based Aquaculture Monitoring System Using Firebase

    Wen-Tsai Sung1, Indra Griha Tofik Isa1,2, Sung-Jung Hsiao3,*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2179-2200, 2023, DOI:10.32604/cmc.2023.041022

    Abstract Indonesia is a producer in the fisheries sector, with production reaching 14.8 million tons in 2022. The production potential of the fisheries sector can be optimally optimized through aquaculture management. One of the most important issues in aquaculture management is how to efficiently control the fish pond water conditions. IoT technology can be applied to support a fish pond aquaculture monitoring system, especially for catfish species (Siluriformes), in real-time and remotely. One of the technologies that can provide this convenience is the IoT. The problem of this study is how to integrate IoT devices with Firebase’s cloud data system to… More >

  • Open Access

    ARTICLE

    Real-Time Memory Data Optimization Mechanism of Edge IoT Agent

    Shen Guo*, Wanxing Sheng, Shuaitao Bai, Jichuan Zhang, Peng Wang

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 799-814, 2023, DOI:10.32604/iasc.2023.038330

    Abstract With the full development of disk-resident databases (DRDB) in recent years, it is widely used in business and transactional applications. In long-term use, some problems of disk databases are gradually exposed. For applications with high real-time requirements, the performance of using disk database is not satisfactory. In the context of the booming development of the Internet of things, domestic real-time databases have also gradually developed. Still, most of them only support the storage, processing, and analysis of data values with fewer data types, which can not fully meet the current industrial process control system data types, complex sources, fast update… More >

  • Open Access

    ARTICLE

    Real-Time Data Transmission with Data Carrier Support Value in Neighbor Strategic Collection in WSN

    S. Ponnarasi1,*, T. Rajendran2

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6039-6057, 2023, DOI:10.32604/cmc.2023.035499

    Abstract An efficient trust-aware secure routing and network strategy-based data collection scheme is presented in this paper to enhance the performance and security of wireless sensor networks during data collection. The method first discovers the routes between the data sensors and the sink node. Several factors are considered for each sensor node along the route, including energy, number of neighbours, previous transmissions, and energy depletion ratio. Considering all these variables, the Sink Reachable Support Measure and the Secure Communication Support Measure, the method evaluates two distinct measures. The method calculates the data carrier support value using these two metrics. A single… More >

  • Open Access

    ARTICLE

    Bitcoin Candlestick Prediction with Deep Neural Networks Based on Real Time Data

    Reem K. Alkhodhairi1, Shahad R. Aljalhami1, Norah K. Rusayni1, Jowharah F. Alshobaili1, Amal A. Al-Shargabi1,*, Abdulatif Alabdulatif2

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3215-3233, 2021, DOI:10.32604/cmc.2021.016881

    Abstract Currently, Bitcoin is the world’s most popular cryptocurrency. The price of Bitcoin is extremely volatile, which can be described as high-benefit and high-risk. To minimize the risk involved, a means of more accurately predicting the Bitcoin price is required. Most of the existing studies of Bitcoin prediction are based on historical (i.e., benchmark) data, without considering the real-time (i.e., live) data. To mitigate the issue of price volatility and achieve more precise outcomes, this study suggests using historical and real-time data to predict the Bitcoin candlestick—or open, high, low, and close (OHLC)—prices. Seeking a better prediction model, the present study… More >

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