Dynamic appliance scheduling and energy management in smart homes using adaptive reinforcement learning techniques

Dynamic appliance scheduling and energy management in smart homes using adaptive reinforcement learning techniques

Abstract Smart home energy management is complicated because of varying user preferences, expenses, and consumption. These dynamics are difficult for traditional systems to handle, but new developments in reinforcement learning and optimization may be able to help. The paper introduces a novel Deman...

Full description

Saved in:
Bibliographic Details
Main Authors: Poonam Saroha, Gopal Singh, Umesh Kumar Lilhore, Sarita Simaiya, Monish Khan, Roobaea Alroobaea, Majed Alsafyani, Hamed Alsufyani
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Demand response
Deep Q network
Self-adaptive Puma optimizer algorithm
Energy consumption
Appliance scheduling
Online Access:https://doi.org/10.1038/s41598-025-08125-9
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-08125-9

Similar Items