A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems

A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems

Abstract The rapid evolution of smart grids, driven by rising global energy demand and renewable energy integration, calls for intelligent, adaptive, and energy-efficient resource allocation strategies. Traditional energy management methods, based on static models or heuristic algorithms, often fail...

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Bibliographic Details
Main Authors: Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada
Format: Article
Language:English
Published: Nature Portfolio 2025-06-01
Series:Scientific Reports
Subjects:
Adaptive learning
Deep learning
Grid optimization
Internet of things
Multi-agent systems
Real-time analytics
Online Access:https://doi.org/10.1038/s41598-025-02649-w
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https://doi.org/10.1038/s41598-025-02649-w

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