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  • Open Access

    ARTICLE

    Forecasting of Appliances House in a Low-Energy Depend on Grey Wolf Optimizer

    Hatim G. Zaini*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2303-2314, 2022, DOI:10.32604/cmc.2022.021998

    Abstract This paper gives and analyses data-driven prediction models for the energy usage of appliances. Data utilized include readings of temperature and humidity sensors from a wireless network. The building envelope is meant to minimize energy demand or the energy required to power the house independent of the appliance and mechanical system efficiency. Approximating a mapping function between the input variables and the continuous output variable is the work of regression. The paper discusses the forecasting framework FOPF (Feature Optimization Prediction Framework), which includes feature selection optimization: by removing non-predictive parameters to choose the best-selected feature hybrid optimization technique has been… More >

  • Open Access

    ARTICLE

    Indoor Electromagnetic Radiation Intensity Relationship to Total Energy of Household Appliances

    Murad A.A. Almekhlafi1, Lamia Osman Widaa2, Fahd N. Al-Wesabi3,*, Mohammad Alamgeer4, Anwer Mustafa Hilal5, Manar Ahmed Hamza5, Abu Sarwar Zamani5, Mohammed Rizwanullah5

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5421-5435, 2022, DOI:10.32604/cmc.2022.019823

    Abstract The rapid technological developments in the modern era have led to increased electrical equipment in our daily lives, work, and homes. From this standpoint, the main objective of this study is to evaluate the potential relationship between the intensity of electromagnetic radiation and the total energy of household appliances in the living environment within the building by measuring and analyzing the strength of the electric field and the entire electromagnetic radiation flux density of electrical devices operating at frequencies (5 Hz to 1 kHz). The living room was chosen as a center for measurement at 15 homes in three different… More >

  • Open Access

    ARTICLE

    Smart Object Detection and Home Appliances Control System in Smart Cities

    Sulaiman Khan1, Shah Nazir1, Habib Ullah Khan2,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 895-915, 2021, DOI:10.32604/cmc.2021.013878

    Abstract During the last decade the emergence of Internet of Things (IoT) based applications inspired the world by providing state of the art solutions to many common problems. From traffic management systems to urban cities planning and development, IoT based home monitoring systems, and many other smart applications. Regardless of these facilities, most of these IoT based solutions are data driven and results in small accuracy values for smaller datasets. In order to address this problem, this paper presents deep learning based hybrid approach for the development of an IoT-based intelligent home security and appliance control system in the smart cities.… More >

  • Open Access

    ARTICLE

    Realization of Internet of Things Smart Appliances

    Jia‐Shing Sheua, I‐Chen Chenb, Yi‐Syong Liaoa

    Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 395-404, 2019, DOI:10.31209/2019.100000101

    Abstract This study proposed a household energy state monitoring system (HESMS) and a household energy load monitoring system (HELMS) for monitoring smart appliances. The HESMS applies reinforcement learning to receive changes in the external environment and the state of an electrical appliance, determines if the electrical appliance should be turned on, and controls the signals sent to the HELMS according to these decisions. The HELMS implements an ON/OFF control mechanism for household appliances according to the control signals and the power consumption state. The proposed systems are based on the wireless communication network and can monitor household appliances’ energy usage, control… More >

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