Anam Mughees^1,2,*, Muhammad Kamran^1,3

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 507-526, 2024, DOI:10.32604/cmc.2024.051820 - 18 July 2024

Abstract Non-intrusive load monitoring is a method that disaggregates the overall energy consumption of a building to estimate the electric power usage and operating status of each appliance individually. Prior studies have mostly concentrated on the identification of high-power appliances like HVAC systems while overlooking the existence of low-power appliances. Low-power consumer appliances have comparable power consumption patterns, which can complicate the detection task and can be mistaken as noise. This research tackles the problem of classification of low-power appliances and uses turn-on current transients to extract novel features and develop unique appliance signatures. A hybrid… More >

Hatim G. Zaini^*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2303-2314, 2022, DOI:10.32604/cmc.2022.021998 - 07 December 2021

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 More >

Murad A.A. Almekhlafi¹, Lamia Osman Widaa², Fahd N. Al-Wesabi^3,*, 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 - 11 October 2021

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… More >

Sulaiman Khan¹, Shah Nazir¹, Habib Ullah Khan^2,*

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 895-915, 2021, DOI:10.32604/cmc.2021.013878 - 12 January 2021

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… More >

Jia‐Shing Sheu^a, I‐Chen Chen^b, Yi‐Syong Liao^a

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 More >