Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique
Energy is an essential contribution for practically all exercises and is, in this way, imperative for development in personal satisfaction. Because of this explanation, valuable energy has turned into an expansion sought after for many years, particularly utilizations in smart homes and structures a...
محفوظ في:
| المؤلف الرئيسي: | |
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| منشور في: |
2021
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://bspace.buid.ac.ae/handle/1234/2000 |
| الوسوم: |
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| _version_ | 1862980615763132416 |
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| author | ALZAABI, HANADI OBAID |
| author_facet | ALZAABI, HANADI OBAID |
| author_role | author |
| dc.creator.none.fl_str_mv | ALZAABI, HANADI OBAID |
| dc.date.none.fl_str_mv | 2021-12 2022-04-26T10:32:11Z 2022-04-26T10:32:11Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 20188576 https://bspace.buid.ac.ae/handle/1234/2000 |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | The British University in Dubai (BUiD) |
| dc.subject.none.fl_str_mv | machine learning smart home fusion energy consumption energy efficiency resource management health monitoring energy management data fusion |
| dc.title.none.fl_str_mv | Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique |
| dc.type.none.fl_str_mv | Dissertation |
| description | Energy is an essential contribution for practically all exercises and is, in this way, imperative for development in personal satisfaction. Because of this explanation, valuable energy has turned into an expansion sought after for many years, particularly utilizations in smart homes and structures as individuals create quickly and improve their way of life dependent on current innovation. The energy requirement is higher than the production of energy, which makes a shortage of energy. Many new plans are being created to satisfy the energy consumer interest. Energy utilization in the housing area is 30-40% of the multitude of areas. A smart home's existence and growth has raised the need for more intelligence in applications such as resource management, energy efficiency, security, and health monitoring so that the home can learn about residents' activities and predict future needs. An energy management technique is being applied in this research work to overcome the challenges of energy consumption optimization. Data fusion has recently attracted much attention for energy efficiency in buildings, where numerous types of information may be processed. The proposed research developed a model by using the data fusion approach to predict energy consumption in terms of accuracy and miss rate. The proposed approach simulation results are being associated with the previously published techniques. Additionally, the prediction accuracy of the anticipated method attains 92%, which is higher than the previous published approaches. |
| id | budr_b6606470a08cfa129c5126beeee1b3d1 |
| identifier_str_mv | 20188576 |
| language_invalid_str_mv | en |
| network_acronym_str | budr |
| network_name_str | The British University in Dubai repository |
| oai_identifier_str | oai:bspace.buid.ac.ae:1234/2000 |
| publishDate | 2021 |
| publisher.none.fl_str_mv | The British University in Dubai (BUiD) |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Intelligent Energy Consumption for Smart Homes using Fused Machine Learning TechniqueALZAABI, HANADI OBAIDmachine learningsmart homefusionenergy consumptionenergy efficiencyresource managementhealth monitoringenergy managementdata fusionEnergy is an essential contribution for practically all exercises and is, in this way, imperative for development in personal satisfaction. Because of this explanation, valuable energy has turned into an expansion sought after for many years, particularly utilizations in smart homes and structures as individuals create quickly and improve their way of life dependent on current innovation. The energy requirement is higher than the production of energy, which makes a shortage of energy. Many new plans are being created to satisfy the energy consumer interest. Energy utilization in the housing area is 30-40% of the multitude of areas. A smart home's existence and growth has raised the need for more intelligence in applications such as resource management, energy efficiency, security, and health monitoring so that the home can learn about residents' activities and predict future needs. An energy management technique is being applied in this research work to overcome the challenges of energy consumption optimization. Data fusion has recently attracted much attention for energy efficiency in buildings, where numerous types of information may be processed. The proposed research developed a model by using the data fusion approach to predict energy consumption in terms of accuracy and miss rate. The proposed approach simulation results are being associated with the previously published techniques. Additionally, the prediction accuracy of the anticipated method attains 92%, which is higher than the previous published approaches.The British University in Dubai (BUiD)2022-04-26T10:32:11Z2022-04-26T10:32:11Z2021-12Dissertationapplication/pdf20188576https://bspace.buid.ac.ae/handle/1234/2000enoai:bspace.buid.ac.ae:1234/20002022-05-19T13:29:12Z |
| spellingShingle | Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique ALZAABI, HANADI OBAID machine learning smart home fusion energy consumption energy efficiency resource management health monitoring energy management data fusion |
| title | Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique |
| title_full | Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique |
| title_fullStr | Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique |
| title_full_unstemmed | Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique |
| title_short | Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique |
| title_sort | Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique |
| topic | machine learning smart home fusion energy consumption energy efficiency resource management health monitoring energy management data fusion |
| url | https://bspace.buid.ac.ae/handle/1234/2000 |