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Quantum Informative Analysis in Smart Power Distribution

Published: 13 November 2024 Publication History

Abstract

Advancements in the Internet of Things (IoT) paradigm have greatly improved the quality of services in the electricity industry through the integration of smart energy distribution and dependable electric devices. Conspicuously, the current research introduces a method for managing electricity consumption in smart residences using IoT-Fog technology, focusing on efficient energy allocation and real-time energy needs. The study specifically examines the effectiveness of electricity grid sub-stations in distributing energy using fog computing technology. By utilizing a quantum computing-assisted approach, optimal energy distribution is achieved by calculating a novel Electricity Usage Measure (EUM) based on actual energy usage patterns of smart homes. Furthermore, the Quantumized Neural Network (QiM-NN) technique is developed to forecast the electricity distribution over grid substations. For performance assessment, 4-month data are collected using four smart houses. Comparative analysis with existing data assessment techniques illustrates the effectiveness in terms of Temporal Delay (6.33 ms), Optimization Performance (Specificity (93.00%), Sensitivity (90.86%), Precision (96.66%), Coverage (96.66 %), Reliability (93.76%), and Stability (71%).

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    Published In

    cover image ACM Transactions on Intelligent Systems and Technology
    ACM Transactions on Intelligent Systems and Technology  Volume 15, Issue 6
    December 2024
    727 pages
    EISSN:2157-6912
    DOI:10.1145/3613712
    • Editor:
    • Huan Liu
    Issue’s Table of Contents

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 13 November 2024
    Online AM: 31 August 2024
    Accepted: 14 August 2024
    Revised: 24 July 2024
    Received: 02 April 2024
    Published in TIST Volume 15, Issue 6

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    Author Tags

    1. Fog Computing
    2. Electricity Distribution
    3. Quantum Neural Network

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