Intelligent Energy Consumption For Smart Homes Using Fused Machine-Learning Technique
Energy is essential to practically all exercises and is imperative for the development of personal satisfaction. So, valuable energy has been in great demand for many years, especially for using smart homes and structures, as individuals quickly improve their way of life depending on current innovat...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , , , , |
| منشور في: |
2022
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://bspace.buid.ac.ae/handle/1234/3042 https://bspace.buid.ac.ae/handle/1234/2000. |
| الوسوم: |
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| _version_ | 1862980611604480000 |
|---|---|
| author | AlZaabi, Hanadi |
| author2 | Shaalan, Khaled M. Ghazal, Taher A. Khan, Muhammad Abbas, Sagheer Mago, Beenu A. A. Tomh, Mohsen Ahmad, Munir |
| author2_role | author author author author author author author |
| author_facet | AlZaabi, Hanadi Shaalan, Khaled M. Ghazal, Taher A. Khan, Muhammad Abbas, Sagheer Mago, Beenu A. A. Tomh, Mohsen Ahmad, Munir |
| author_role | author |
| dc.creator.none.fl_str_mv | AlZaabi, Hanadi Shaalan, Khaled M. Ghazal, Taher A. Khan, Muhammad Abbas, Sagheer Mago, Beenu A. A. Tomh, Mohsen Ahmad, Munir |
| dc.date.none.fl_str_mv | 2022 2025-05-14T13:23:35Z 2025-05-14T13:23:35Z |
| dc.identifier.none.fl_str_mv | ALZAABI, HANADI OBAID (2021) Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique. dissertation. The British University in Dubai (BUiD). https://bspace.buid.ac.ae/handle/1234/3042 https://bspace.buid.ac.ae/handle/1234/2000. |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | Tech science press |
| dc.relation.none.fl_str_mv | Computers, Materials and Continua |
| dc.subject.none.fl_str_mv | Energy consumption; intelligent; machine learning; technique; smart homes; prediction |
| dc.title.none.fl_str_mv | Intelligent Energy Consumption For Smart Homes Using Fused Machine-Learning Technique |
| dc.type.none.fl_str_mv | Article |
| description | Energy is essential to practically all exercises and is imperative for the development of personal satisfaction. So, valuable energy has been in great demand for many years, especially for using smart homes and structures, as individuals quickly improve their way of life depending on current innovations. However, there is a shortage of energy, as the energy required is higher than that produced. Many new plans are being designed to meet the consumer’s energy requirements. In many regions, energy utilization in the housing area is 30%–40%. The growth of smart homes has raised the requirement for intelligence in applications such as asset management, energy-efficient automation, security, and healthcare monitoring to learn about residents’ actions and forecast their future demands. To overcome the challenges of energy consumption optimization, in this study, we apply an energy management technique. Data fusion has recently attracted much energy efficiency in buildings, where numerous types of information are processed. The proposed research developed a data fusion model to predict energy consumption for accuracy and miss rate. The results of the proposed approach are compared with those of the previously published techniques and found that the prediction accuracy of the proposed method is 92%, which is higher than the previously published approaches. |
| id | budr_fac9b4fa7fb0d950ea14a1d0b7f78439 |
| identifier_str_mv | ALZAABI, HANADI OBAID (2021) Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique. dissertation. The British University in Dubai (BUiD). |
| 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:1234/3042 |
| publishDate | 2022 |
| publisher.none.fl_str_mv | Tech science press |
| 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, HanadiShaalan, KhaledM. Ghazal, TaherA. Khan, MuhammadAbbas, SagheerMago, BeenuA. A. Tomh, MohsenAhmad, MunirEnergy consumption; intelligent; machine learning; technique; smart homes; predictionEnergy is essential to practically all exercises and is imperative for the development of personal satisfaction. So, valuable energy has been in great demand for many years, especially for using smart homes and structures, as individuals quickly improve their way of life depending on current innovations. However, there is a shortage of energy, as the energy required is higher than that produced. Many new plans are being designed to meet the consumer’s energy requirements. In many regions, energy utilization in the housing area is 30%–40%. The growth of smart homes has raised the requirement for intelligence in applications such as asset management, energy-efficient automation, security, and healthcare monitoring to learn about residents’ actions and forecast their future demands. To overcome the challenges of energy consumption optimization, in this study, we apply an energy management technique. Data fusion has recently attracted much energy efficiency in buildings, where numerous types of information are processed. The proposed research developed a data fusion model to predict energy consumption for accuracy and miss rate. The results of the proposed approach are compared with those of the previously published techniques and found that the prediction accuracy of the proposed method is 92%, which is higher than the previously published approaches.Tech science press2025-05-14T13:23:35Z2025-05-14T13:23:35Z2022ArticleALZAABI, HANADI OBAID (2021) Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique. dissertation. The British University in Dubai (BUiD).https://bspace.buid.ac.ae/handle/1234/3042https://bspace.buid.ac.ae/handle/1234/2000.enComputers, Materials and Continuaoai:bspace.buid.ac.ae:1234/30422025-05-14T14:21:41Z |
| spellingShingle | Intelligent Energy Consumption For Smart Homes Using Fused Machine-Learning Technique AlZaabi, Hanadi Energy consumption; intelligent; machine learning; technique; smart homes; prediction |
| 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 | Energy consumption; intelligent; machine learning; technique; smart homes; prediction |
| url | https://bspace.buid.ac.ae/handle/1234/3042 https://bspace.buid.ac.ae/handle/1234/2000. |