Repository logo
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
Repository logo
  • Communities & Collections
  • All of BSpace
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "ALZAABI, HANADI OBAID"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    Item
    Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique
    (The British University in Dubai (BUiD), 2021-12) ALZAABI, HANADI OBAID
    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.
  • Library Website
  • University Website
The British University in Dubai (BUiD)

PO Box 345015 | 1st & 2nd Floors, Block 11, Dubai International Academic City (DIAC)
United Arab Emirates, Phone: +971 4 279 1471, Email: library@buid.ac.ae

DSpace software copyright © 2002-2025 LYRASIS

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback