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The Importance of AI-Enabled Internet of everything Services for Smart Home Management Cover

The Importance of AI-Enabled Internet of everything Services for Smart Home Management

International Journal on Smart Sensing and Intelligent Systems
Volume 17 (2024): Issue 1 (January 2024)
By: Abdullah Bajahzar  
Open Access
|Jul 2024

Figures & Tables

Figure 1:

Proposed AI-IoES model. AI-IoES, AI-enabled Internet of everything services.
Proposed AI-IoES model. AI-IoES, AI-enabled Internet of everything services.

Figure 2:

DNN model. DNN, deep neural network.
DNN model. DNN, deep neural network.

Figure 3:

Sequence diagram of IoE-based smart home energy monitoring system. IoE, Internet of everything.
Sequence diagram of IoE-based smart home energy monitoring system. IoE, Internet of everything.

Figure 4:

EER. AI-IoES, AI-enabled Internet of everything services; EER, energy efficiency ratio; FES-EESHM, fuzzy expert systems efficient energy smart home management system; HRSO, hybrid robust-stochastic optimization; MARL-DDM, multi-agent reinforcement learning based data-driven methods; MORL, multi-objective reinforcement learning.
EER. AI-IoES, AI-enabled Internet of everything services; EER, energy efficiency ratio; FES-EESHM, fuzzy expert systems efficient energy smart home management system; HRSO, hybrid robust-stochastic optimization; MARL-DDM, multi-agent reinforcement learning based data-driven methods; MORL, multi-objective reinforcement learning.

Figure 5:

User experience ratio. AI-IoES, AI-enabled Internet of everything services; FES-EESHM, fuzzy expert systems efficient energy smart home management system; HRSO, hybrid robust-stochastic optimization; MARL-DDM, multi-agent reinforcement learning based data-driven methods; MORL, multi-objective reinforcement learning.
User experience ratio. AI-IoES, AI-enabled Internet of everything services; FES-EESHM, fuzzy expert systems efficient energy smart home management system; HRSO, hybrid robust-stochastic optimization; MARL-DDM, multi-agent reinforcement learning based data-driven methods; MORL, multi-objective reinforcement learning.

Figure 6:

Energy consumption rate. AI-IoES, AI-enabled Internet of everything services; FES-EESHM, fuzzy expert systems efficient energy smart home management system; HRSO, hybrid robust-stochastic optimization; MARL-DDM, multi-agent reinforcement learning based data-driven methods; MORL, multi-objective reinforcement learning.
Energy consumption rate. AI-IoES, AI-enabled Internet of everything services; FES-EESHM, fuzzy expert systems efficient energy smart home management system; HRSO, hybrid robust-stochastic optimization; MARL-DDM, multi-agent reinforcement learning based data-driven methods; MORL, multi-objective reinforcement learning.

Figure 7:

Accuracy ratio. AI-IoES, AI-enabled Internet of everything services; FES-EESHM, fuzzy expert systems efficient energy smart home management system; HRSO, hybrid robust-stochastic optimization; MARL-DDM, multi-agent reinforcement learning based data-driven methods; MORL, multi-objective reinforcement learning.
Accuracy ratio. AI-IoES, AI-enabled Internet of everything services; FES-EESHM, fuzzy expert systems efficient energy smart home management system; HRSO, hybrid robust-stochastic optimization; MARL-DDM, multi-agent reinforcement learning based data-driven methods; MORL, multi-objective reinforcement learning.
DOI: https://doi.org/10.2478/ijssis-2024-0026 | Journal eISSN: 1178-5608
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Language: English
Submitted on: Mar 2, 2024
|
Published on: Jul 23, 2024
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
artificial intelligence,
Internet of everything,
smart home management,
energy management
Related subjects:
Engineering,
Introductions and overviews,
Engineering, other

© 2024 Abdullah Bajahzar, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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