A Novel Framework for AI-Driven, Cloud-Integrated Energy-Efficient IoT Solutions in Smart Homes

Smart homes are defined with high needs of energy efficiency in home automation to which the IoT technologies are combined with Artificial Intelligence (AI) and the cloud computing system. That is why this research has posed the prospect of a new framework focused on the application of Artificial Intelligence and cloud solutions to manage energy usage in smart homes. The system harnesses data from smart IoT applications, statistical research and self-adjusting control to minimize energy consumption while providing comfort and satisfaction to the user. Based on initial experiments carried out in a smart home test bed, the proposed approach achieved peak hour energy savings of up to 20%. Due to the AI model’s prediction accuracy, which was within 5% of actual usage, one could effectively manage smart devices. Furthermore, the cloud-base architecture also empowered the system’s scalability and adequate time consumption with the response time below 0.10 seconds for value added tasks and 5 seconds for critical tasks. The proposed strategy allows improving energy efficiency with further transition to smart home concepts while being applied as a long-term decision.

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Publication Details

Published
2024-11-06
DOI
https://doi.org/10.1109/iceca63461.2024.10800957
Citations
1
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.35
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article

A Novel Framework for AI-Driven, Cloud-Integrated Energy-Efficient IoT Solutions in Smart Homes

Ratidev Samal, P. Bhaskara Reddy, Dankan Gowda, Ravikiran Kamath Billady et al.
1 citations
IoT and Edge/Fog Computing
0.35
article

A Novel Framework for AI-Driven, Cloud-Integrated Energy-Efficient IoT Solutions in Smart Homes

Ratidev Samal, P. Bhaskara Reddy, Dankan Gowda, Ravikiran Kamath Billady, P.V. Rajlakshmi, A.V.G.A. Marthanda
article en
1 citations

Abstract

Smart homes are defined with high needs of energy efficiency in home automation to which the IoT technologies are combined with Artificial Intelligence (AI) and the cloud computing system. That is why this research has posed the prospect of a new framework focused on the application of Artificial Intelligence and cloud solutions to manage energy usage in smart homes. The system harnesses data from smart IoT applications, statistical research and self-adjusting control to minimize energy consumption while providing comfort and satisfaction to the user. Based on initial experiments carried out in a smart home test bed, the proposed approach achieved peak hour energy savings of up to 20%. Due to the AI model’s prediction accuracy, which was within 5% of actual usage, one could effectively manage smart devices. Furthermore, the cloud-base architecture also empowered the system’s scalability and adequate time consumption with the response time below 0.10 seconds for value added tasks and 5 seconds for critical tasks. The proposed strategy allows improving energy efficiency with further transition to smart home concepts while being applied as a long-term decision.

Nitte University (IN), Jawaharlal Nehru Technological University, Kakinada (IN), Centurion University of Technology and Management (IN)
Affordable and clean energy
Openalex Percentile: Top 35%
IoT and Edge/Fog Computing
0.35
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A Novel Framework for AI-Driven, Cloud-Integrated Energy-Efficient IoT Solutions in Smart Homes — Ratidev Samal, P. Bhaskara Reddy, et al. · (2024) | TGRS Research Map | TGRS