Main Page
Deanship
The Dean
Dean's Word
Curriculum Vitae
Contact the Dean
Vision and Mission
Organizational Structure
Vice- Deanship
Vice- Dean
KAU Graduate Studies
Research Services & Courses
Research Services Unit
Important Research for Society
Deanship's Services
FAQs
Research
Staff Directory
Files
Favorite Websites
Deanship Access Map
Graduate Studies Awards
Deanship's Staff
Staff Directory
Files
Researches
Contact us
عربي
English
About
Admission
Academic
Research and Innovations
University Life
E-Services
Search
Deanship of Graduate Studies
Document Details
Document Type
:
Thesis
Document Title
:
Machine Learning Based User Activity Analysis and Behavior Evaluation for More Energy Efficient Environments
تحليل نشاط المستخدم وتقييم سلوكه المبني على تعلم الالة لبيئات أكثر كفاءة في استخدام الطاقة
Subject
:
Faculty of Computing and Information Technology
Document Language
:
Arabic
Abstract
:
In recent years, energy consumption has considerably increased worldwide. One of the most notable reasons is the rapid increase of electronic and internet of things devices used in various forms into smart homes and smart appliances. However, such devices are not the merely cause of the large waste of energy, but rather how they are used by users in daily life. In this paper, we propose an approach to solve the wasteful energy consumption issue by analyzing the user side activities to enable addressing their adverse behaviors. Thus, different machine learning techniques are devoted for monitoring such users’ activities in an environment of interest to perceive, rate, and rank both activities and users upon three levels of energy consumers as green, balanced, and wasteful based on their observed interactions with electrical devices in that environment. Subsequently, a software architecture design can be accordingly recommended by which considers suggesting tips for the user to correct their wasteful behavior or shifting them from balanced level to better green saving level. As such, by encouraging them for becoming more energy conscious users, this in turn can make the environment, in which the proposed system is implemented, a more energy wise environment.
Supervisor
:
Dr. Emad Sami Jaha
Thesis Type
:
Master Thesis
Publishing Year
:
1444 AH
2023 AD
Added Date
:
Thursday, April 27, 2023
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
عمر عبدالعزيز العرينان
Alorainan, Omar Abdulaziz
Researcher
Master
Files
File Name
Type
Description
49159.pdf
pdf
Back To Researches Page